Nothing
#' Generate a List of Available Cell Blocks
#'
#' This function creates and returns a named list of cell blocks,
#' where each name corresponds to a descriptive label of the cell block,
#' and the value is the function name associated with that cell block.
#'
#' @return A named list where each name is a string describing a cell block
#' (e.g., "T2 Cell Block 1.1") and each value is a string corresponding
#' to the function name (e.g., "replext_t2_c1.1") that is associated with
#' the simulation process for that particular cell block.
#'
#' @keywords internal
getCellBlocks <- function(){
list("T2 Cell Block 1.1" = "replext_t2_c1.1",
"T2 Cell Block 1.2" = "replext_t2_c1.2",
"T2 Cell Block 2.1" = "replext_t2_c2.1",
"T2 Cell Block 2.2" = "replext_t2_c2.2",
"T2 Cell Block 3.1" = "replext_t2_c3.1",
"T2 Cell Block 3.2" = "replext_t2_c3.2",
"T2 Cell Block 4.1" = "replext_t2_c4.1",
"T2 Cell Block 4.2" = "replext_t2_c4.2",
"T3 Cell Block 1.1" = "replext_t3_c1.1",
"T3 Cell Block 1.2" = "replext_t3_c1.2",
"T3 Cell Block 2.1" = "replext_t3_c2.1",
"T3 Cell Block 2.2" = "replext_t3_c2.2",
"T3 Cell Block 3.1" = "replext_t3_c3.1",
"T3 Cell Block 3.2" = "replext_t3_c3.2",
"T3 Cell Block 4.1" = "replext_t3_c4.1",
"T3 Cell Block 4.2" = "replext_t3_c4.2",
"T4 Cell Block 1.1" = "replext_t4_c1.1",
"T4 Cell Block 2.1" = "replext_t4_c2.1",
"T4 Cell Block 3.1" = "replext_t4_c3.1",
"T4 Cell Block 4.1" = "replext_t4_c4.1",
"T4 Cell Block 5.1" = "replext_t4_c5.1",
"T4 Cell Block 6.1" = "replext_t4_c6.1",
"T4 Cell Block 7.1" = "replext_t4_c7.1",
"T5 Cell Block 1.1" = "replext_t5_c1.1",
"T5 Cell Block 1.2" = "replext_t5_c1.2",
"T5 Cell Block 1.3" = "replext_t5_c1.3",
"T5 Cell Block 2.1" = "replext_t5_c2.1",
"T5 Cell Block 2.2" = "replext_t5_c2.2",
"T5 Cell Block 2.3" = "replext_t5_c2.3",
"T6 Cell Block 1.1" = "replext_t6_c1.1",
"T6 Cell Block 1.2" = "replext_t6_c1.2",
"T6 Cell Block 1.3" = "replext_t6_c1.3",
"T6 Cell Block 2.1" = "replext_t6_c2.1",
"T6 Cell Block 2.2" = "replext_t6_c2.2",
"T6 Cell Block 2.3" = "replext_t6_c2.3",
"TS1 Cell Block 1.1" = "replext_ts1_c1.1",
"TS1 Cell Block 2.1" = "replext_ts1_c2.1",
"TS1 Cell Block 3.1" = "replext_ts1_c3.1",
"TS2 Cell Block 1.1" = "replext_ts2_c1.1",
"TS2 Cell Block 1.2" = "replext_ts2_c1.2",
"TS2 Cell Block 2.1" = "replext_ts2_c2.1",
"TS2 Cell Block 2.2" = "replext_ts2_c2.2",
"TS2 Cell Block 3.1" = "replext_ts2_c3.1",
"TS2 Cell Block 3.2" = "replext_ts2_c3.2",
"TS2 Cell Block 4.1" = "replext_ts2_c4.1",
"TS2 Cell Block 4.2" = "replext_ts2_c4.2",
"TS3 Cell Block 1.1" = "replext_ts3_c1.1",
"TS3 Cell Block 1.2" = "replext_ts3_c1.2",
"TS3 Cell Block 2.1" = "replext_ts3_c2.1",
"TS3 Cell Block 2.2" = "replext_ts3_c2.2",
"TS3 Cell Block 3.1" = "replext_ts3_c3.1",
"TS3 Cell Block 3.2" = "replext_ts3_c3.2",
"TS3 Cell Block 4.1" = "replext_ts3_c4.1",
"TS3 Cell Block 4.2" = "replext_ts3_c4.2")
}
#' Generate UI Elements for Selected Cell Block
#'
#' This function generates a dynamic user interface (UI) for the Shiny app based on the selected cell block.
#' It creates a list of Shiny UI elements, such as numeric inputs and text inputs,
#' tailored to the requirements of the chosen cell block.
#'
#' @param cellBlock A character string identifying the selected cell block.
#' The function uses this parameter to determine which set of UI elements to generate.
#'
#' @return A list of Shiny UI elements specific to the selected cell block.
#' These UI elements include numeric inputs, text inputs, and other relevant controls
#' required to capture user inputs for simulation parameters.
#'
#' @keywords internal
getUIParams <- function(cellBlock) {
switch(cellBlock,
"replext_t2_c1.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = NA),
shiny::numericInput("Sk2", "Skew for the second group:", value = NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t2_c1.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = NA),
shiny::numericInput("Sk2", "Skew for the second group:", value = NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t2_c2.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t2_c2.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t2_c3.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t2_c3.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t2_c4.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "3"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t2_c4.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "3"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t3_c1.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = NA),
shiny::numericInput("Sk2", "Skew for the second group:", value = NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t3_c1.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = NA),
shiny::numericInput("Sk2", "Skew for the second group:", value = NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t3_c2.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t3_c2.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t3_c3.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t3_c3.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t3_c4.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "3"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t3_c4.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "3"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t4_c1.1" = list(shiny::textInput("rdist", "Distribution type:", "rlnorm"),
shiny::numericInput("par1_1", "meanlog Group 1:", 1),
shiny::numericInput("par2_1", "sdlog Group1:", 0.6),
shiny::numericInput("par1_2", "meanlog Group 2:", 2),
shiny::numericInput("par2_2", "sdlog Group2:", 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t4_c2.1" = list(shiny::textInput("rdist", "Distribution type:", "rpois"),
shiny::numericInput("par1_1", "lambda Group 1:", 5),
#shiny::numericInput("par2_1", "not applicable", NA),
shiny::numericInput("par1_2", "lambda Group 2:", 10),
#shiny::numericInput("par2_2", "not applicable", NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t4_c3.1" = list(shiny::textInput("rdist", "Distribution type:", "rchisq"),
shiny::numericInput("par1_1", "dof Group 1:", 1),
shiny::numericInput("par2_1", "ncp Group 1", 0),
shiny::numericInput("par1_2", "dof Group 2:", 6),
shiny::numericInput("par2_2", "ncp Group 2", 0),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t4_c4.1" = list(shiny::textInput("rdist", "Distribution type:", "rlnorm"),
shiny::numericInput("par1_1", "meanlog Group 1:", 1),
shiny::numericInput("par2_1", "sdlog Group1:", 0.6),
shiny::numericInput("par1_2", "meanlog Group 2:", 3),
shiny::numericInput("par2_2", "sdlog Group2:", 4),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t4_c5.1" = list(shiny::textInput("rdist", "Distribution type:", "rcauchy"),
shiny::numericInput("par1_1", "location Group 1:", 5),
shiny::numericInput("par2_1", "scale Group1:", 2),
shiny::numericInput("par1_2", "location Group 2:", 10),
shiny::numericInput("par2_2", "scale Group2:", 4),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t4_c6.1" = list(shiny::textInput("rdist", "Distribution type:", "rchisq,rpois"),
shiny::numericInput("par1_1", "dof Group 1:", 6),
shiny::numericInput("par2_1", "ncp Group1:", 0),
shiny::numericInput("par1_2", "lambda Group 2:", 10),
#shiny::numericInput("par2_2", "scale Group2:", NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t4_c7.1" = list(shiny::textInput("rdist", "Distribution type:", "rlnorm,rchisq"),
shiny::numericInput("par1_1", "meanlog Group 1:", 1),
shiny::numericInput("par2_1", "sdlog Group1:", 0.6),
shiny::numericInput("par1_2", "dof Group 2:", 6),
shiny::numericInput("par2_2", "ncp Group2:", 0),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t5_c1.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t5_c1.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t5_c1.3" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.5),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.5),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t5_c2.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.5),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.5),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t5_c2.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.2),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t5_c2.3" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.2),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t6_c1.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t6_c1.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t6_c1.3" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.5),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.5),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t6_c2.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.5),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.5),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t6_c2.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.2),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_t6_c2.3" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 7),
shiny::numericInput("S2", "Standard deviation for the second group:", 3),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.2),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("correl", "Correlation between the groups:", value = 0.8),
shiny::textInput("n", "Sample size:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts1_c1.1" = list(shiny::textInput("rdist", "Distribution type:", "rlnorm"),
shiny::numericInput("par1_1", "meanlog Group 1:", 1),
shiny::numericInput("par2_1", "sdlog Group1:", 0.6),
shiny::numericInput("par1_2", "meanlog Group 2:", 1),
shiny::numericInput("par2_2", "sdlog Group2:", 0.6),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts1_c2.1" = list(shiny::textInput("rdist", "Distribution type:", "rpois"),
shiny::numericInput("par1_1", "lambda Group 1:", 5),
#shiny::numericInput("par2_1", "not applicable", NA),
shiny::numericInput("par1_2", "lambda Group 2:", 5),
#shiny::numericInput("par2_2", "not applicable", NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts1_c3.1" = list(shiny::textInput("rdist", "Distribution type:", "rchisq"),
shiny::numericInput("par1_1", "dof Group 1:", 3),
shiny::numericInput("par2_1", "ncp Group 1", 0),
shiny::numericInput("par1_2", "dof Group 2:", 3),
shiny::numericInput("par2_2", "ncp Group 2", 0),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts2_c1.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("M3", "Mean for the third group:", 5),
shiny::numericInput("S3", "Standard deviation for the third group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = NA),
shiny::numericInput("Sk2", "Skew for the second group:", value = NA),
shiny::numericInput("Sk3", "Skew for the third group:", value = NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts2_c1.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 2),
shiny::numericInput("M3", "Mean for the third group:", 5),
shiny::numericInput("S3", "Standard deviation for the third group:", 4),
shiny::numericInput("Sk1", "Skew for the first group:", value = NA),
shiny::numericInput("Sk2", "Skew for the second group:", value = NA),
shiny::numericInput("Sk3", "Skew for the third group:", value = NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts2_c2.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("M3", "Mean for the third group:", 5),
shiny::numericInput("S3", "Standard deviation for the third group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts2_c2.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 2),
shiny::numericInput("M3", "Mean for the third group:", 5),
shiny::numericInput("S3", "Standard deviation for the third group:", 4),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts2_c3.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("M3", "Mean for the third group:", 5),
shiny::numericInput("S3", "Standard deviation for the third group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts2_c3.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 2),
shiny::numericInput("M3", "Mean for the third group:", 5),
shiny::numericInput("S3", "Standard deviation for the third group:", 4),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts2_c4.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("M3", "Mean for the third group:", 5),
shiny::numericInput("S3", "Standard deviation for the third group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "3"),
shiny::textInput("n2", "Sample sizes for the second group:", "4"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts2_c4.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 5),
shiny::numericInput("S2", "Standard deviation for the second group:", 2),
shiny::numericInput("M3", "Mean for the third group:", 5),
shiny::numericInput("S3", "Standard deviation for the third group:", 4),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "3"),
shiny::textInput("n2", "Sample sizes for the second group:", "4"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts3_c1.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 6),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("M3", "Mean for the third group:", 7),
shiny::numericInput("S3", "Standard deviation for the third group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = NA),
shiny::numericInput("Sk2", "Skew for the second group:", value = NA),
shiny::numericInput("Sk3", "Skew for the third group:", value = NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts3_c1.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 6),
shiny::numericInput("S2", "Standard deviation for the second group:", 2),
shiny::numericInput("M3", "Mean for the third group:", 7),
shiny::numericInput("S3", "Standard deviation for the third group:", 4),
shiny::numericInput("Sk1", "Skew for the first group:", value = NA),
shiny::numericInput("Sk2", "Skew for the second group:", value = NA),
shiny::numericInput("Sk3", "Skew for the third group:", value = NA),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts3_c2.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 6),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("M3", "Mean for the third group:", 7),
shiny::numericInput("S3", "Standard deviation for the third group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts3_c2.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 6),
shiny::numericInput("S2", "Standard deviation for the second group:", 2),
shiny::numericInput("M3", "Mean for the third group:", 7),
shiny::numericInput("S3", "Standard deviation for the third group:", 4),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts3_c3.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 6),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("M3", "Mean for the third group:", 7),
shiny::numericInput("S3", "Standard deviation for the third group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts3_c3.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 6),
shiny::numericInput("S2", "Standard deviation for the second group:", 2),
shiny::numericInput("M3", "Mean for the third group:", 7),
shiny::numericInput("S3", "Standard deviation for the third group:", 4),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 1),
shiny::textInput("n1", "Sample sizes for the first group:", "5"),
shiny::textInput("n2", "Sample sizes for the second group:", "5"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts3_c4.1" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 6),
shiny::numericInput("S2", "Standard deviation for the second group:", 1),
shiny::numericInput("M3", "Mean for the third group:", 7),
shiny::numericInput("S3", "Standard deviation for the third group:", 1),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "3"),
shiny::textInput("n2", "Sample sizes for the second group:", "4"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95)),
"replext_ts3_c4.2" = list(shiny::numericInput("M1", "Mean for the first group:", 5),
shiny::numericInput("S1", "Standard deviation for the first group:", 1),
shiny::numericInput("M2", "Mean for the second group:", 6),
shiny::numericInput("S2", "Standard deviation for the second group:", 2),
shiny::numericInput("M3", "Mean for the third group:", 7),
shiny::numericInput("S3", "Standard deviation for the third group:", 4),
shiny::numericInput("Sk1", "Skew for the first group:", value = 0.8),
shiny::numericInput("Sk2", "Skew for the second group:", value = 0.8),
shiny::numericInput("Sk3", "Skew for the third group:", value = 0.8),
shiny::textInput("n1", "Sample sizes for the first group:", "3"),
shiny::textInput("n2", "Sample sizes for the second group:", "4"),
shiny::textInput("n3", "Sample sizes for the third group:", "5"),
shiny::numericInput("n_simulations", "Number of simulation iterations:", 10),
shiny::numericInput("nboot", "Number of bootstrap iterations:", 1000),
shiny::numericInput("conf.level", "Confidence level:", 0.95))
)
}
#' Append Input Parameters to Data Frame
#'
#' This internal function appends the input parameters and a unique run code to the data frame of simulation results.
#' It creates a comprehensive data frame that includes both the results and the parameters used for the simulation,
#' facilitating easier tracking and analysis of the simulation runs.
#'
#' @param df A data frame containing the simulation results.
#' @param input A list of input parameters used in the simulation, typically sourced from the Shiny app's user inputs.
#'
#' @return A data frame that combines the original simulation results with the input parameters used in the simulation.
#' Additionally, a unique run code is generated and appended to each row for identification purposes.
#'
#' @keywords internal
appendInputParams <- function(df, input) {
# Generate a unique code for the simulation run
run_code <- mmints::generateRunCode()
# Create a data frame of input parameters
if (grepl("^replext_t2_", input$cellBlock) || grepl("^replext_t3_", input$cellBlock)) {
params_df <- data.frame(
M1 = input$M1, S1 = input$S1, M2 = input$M2, S2 = input$S2,
Sk1 = input$Sk1, Sk2 = input$Sk2,
n_simulations = input$n_simulations, nboot = input$nboot,
conf.level = input$conf.level, cellblock = input$cellBlock, RunCode = run_code,
stringsAsFactors = FALSE
)
} else if (grepl("^replext_t4_", input$cellBlock) || grepl("^replext_ts1_", input$cellBlock)) {
params_df <- data.frame(
rdist = toString(text_to_char_vector(input$rdist)),
par1_1 = input$par1_1, par2_1 = mmints::vec_null(input$par2_1),
par1_2 = input$par1_2, par2_2 = mmints::vec_null(input$par2_2),
n_simulations = input$n_simulations, nboot = input$nboot,
conf.level = input$conf.level, cellblock = input$cellBlock,
RunCode = run_code, stringsAsFactors = FALSE
)
# make sure rpois values for par2 are null in the database
if (input$rdist == "rpois"){
params_df$par2_1 <- NULL
params_df$par2_2 <- NULL
}
if (length(text_to_char_vector(input$rdist)) == 2){
if(text_to_char_vector(input$rdist)[1] == "rpois"){
params_df$par2_1 <- NULL
}
if(text_to_char_vector(input$rdist)[2] == "rpois"){
params_df$par2_2 <- NULL
}
}
} else if (grepl("^replext_t5_", input$cellBlock) || grepl("^replext_t6_", input$cellBlock)) {
params_df <- data.frame(
M1 = input$M1, S1 = input$S1, M2 = input$M2, S2 = input$S2,
Sk1 = input$Sk1, Sk2 = input$Sk2,
correl = input$correl,
n_simulations = input$n_simulations, nboot = input$nboot,
conf.level = input$conf.level, cellblock = input$cellBlock,
RunCode = run_code, stringsAsFactors = FALSE
)
} else if (grepl("^replext_ts2_", input$cellBlock) || grepl("^replext_ts3_", input$cellBlock)) {
params_df <- data.frame(
M1 = input$M1, S1 = input$S1, M2 = input$M2, S2 = input$S2,
M3 = input$M3, S3 = input$S3,
Sk1 = input$Sk1, Sk2 = input$Sk2,
Sk3 = input$Sk3,
n_simulations = input$n_simulations, nboot = input$nboot,
conf.level = input$conf.level, cellblock = input$cellBlock,
RunCode = run_code, stringsAsFactors = FALSE
)
} else {
stop("Must select a supported cell block")
}
# Repeat the parameters data frame to match the number of rows in df
params_df <- params_df[rep(1, nrow(df)), ]
# Change name of conf.level to conf
colnames(params_df)[which(names(params_df) == "conf.level")] <- "conf"
# Combine with the simulation results
cbind(df, params_df)
}
#' Execute Simulation Based on User Inputs
#'
#' This internal function manages the simulation process in a Shiny app environment.
#' It dynamically selects the appropriate simulation function based on the selected cell block
#' and passes user inputs to this function. The function also handles the setting of a random
#' number seed, if provided, to ensure reproducibility of results.
#'
#' @param input A list of inputs gathered from the Shiny app's UI, including the selected
#' cell block and other parameters necessary for the simulation.
#'
#' @return The result of the simulation function that corresponds to the selected cell block.
#' This result is typically a data frame containing the outcomes of the simulation.
#'
#' @keywords internal
runSimulation <- function(input) {
# Dynamically call the appropriate function based on the cell block prefix
if (grepl("^replext_t2_", input$cellBlock) || grepl("^replext_t3_", input$cellBlock)) {
return(replext_t2_c1.1(M1 = input$M1, S1 = input$S1, M2 = input$M2, S2 = input$S2,
Sk1 = mmints::vec_null(input$Sk1), Sk2 = mmints::vec_null(input$Sk2),
n1 = mmints::text_to_vector(input$n1), n2 = mmints::text_to_vector(input$n2),
n_simulations = input$n_simulations, nboot = input$nboot,
conf.level = input$conf.level))
} else if (grepl("^replext_t4_", input$cellBlock) || grepl("^replext_ts1_", input$cellBlock)) {
return(replext_t4_c1.1(rdist = text_to_char_vector(input$rdist), par1_1 = input$par1_1, par2_1 = mmints::vec_null(input$par2_1),
par1_2 = input$par1_2, par2_2 = mmints::vec_null(input$par2_2),
n1 = mmints::text_to_vector(input$n1),
n2 = mmints::text_to_vector(input$n2),
n_simulations = input$n_simulations, nboot = input$nboot,
conf.level = input$conf.level))
} else if (grepl("^replext_t5_", input$cellBlock) || grepl("^replext_t6_", input$cellBlock)) {
return(replext_t5_c1.1(M1 = input$M1, S1 = input$S1, M2 = input$M2, S2 = input$S2,
Sk1 = mmints::vec_null(input$Sk1), Sk2 = mmints::vec_null(input$Sk2),
correl = input$correl, n = mmints::text_to_vector(input$n),
n_simulations = input$n_simulations, nboot = input$nboot,
conf.level = input$conf.level))
} else if (grepl("^replext_ts2_", input$cellBlock) || grepl("^replext_ts3_", input$cellBlock)) {
return(replext_ts2_c1.1(M1 = input$M1, S1 = input$S1, M2 = input$M2, S2 = input$S2,
M3 = input$M3, S3 = input$S3,
Sk1 = mmints::vec_null(input$Sk1), Sk2 = mmints::vec_null(input$Sk2),
Sk3 = mmints::vec_null(input$Sk3),
n1 = mmints::text_to_vector(input$n1), n2 = mmints::text_to_vector(input$n2),
n3 = mmints::text_to_vector(input$n3),
n_simulations = input$n_simulations, nboot = input$nboot,
conf.level = input$conf.level))
} else {
stop("Must select a supported cell block")
}
}
#' Convert Comma-Separated String to Character Vector
#'
#' This internal function takes a string of comma-separated values and
#' converts it into a character vector. It is used to process user inputs
#' from the Shiny app's UI, particularly when these inputs need to be
#' retained as character data.
#'
#' @param text_input A string containing comma-separated values,
#' typically user input from the Shiny app's UI. The function
#' trims leading and trailing whitespace before processing.
#'
#' @return A character vector converted from the comma-separated string.
#' If the input is an empty string or consists only of whitespace,
#' returns an empty character vector.
#'
#' @keywords internal
text_to_char_vector <- function(text_input) {
strsplit(trimws(text_input), ",")[[1]]
}
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