plot_sim_ext: Plot Simulated Data and Target External Data for Continuous...

In SimMultiCorrData: Simulation of Correlated Data with Multiple Variable Types

Description

This plots simulated continuous or count data and overlays external data, both as histograms. The external data is a required input. The simulated data is centered and scaled to have the same mean and variance as the external data set. If the user wants to only plot simulated data, plot_sim_theory should be used instead with overlay = FALSE. It returns a ggplot2-package object so the user can modify as necessary. The graph parameters (i.e. title, power_color, target_color, nbins) are ggplot2-package parameters. It works for valid or invalid power method pdfs.

Usage

plot_sim_ext(sim_y, title = "Simulated Data Values", ylower = NULL,
  yupper = NULL, power_color = "dark blue", ext_y = NULL,
  target_color = "dark green", nbins = 100, legend.position = c(0.975,
  0.9), legend.justification = c(1, 1), legend.text.size = 10,
  title.text.size = 15, axis.text.size = 10, axis.title.size = 13)

Arguments

sim_y	a vector of simulated data
title	the title for the graph (default = "Simulated Data Values")
ylower	the lower y value to use in the plot (default = NULL, uses minimum simulated y value)
yupper	the upper y value (default = NULL, uses maximum simulated y value)
power_color	the histogram fill color for the simulated variable (default = "dark blue")
ext_y	a vector of external data (required)
target_color	the histogram fill color for the target data (default = "dark green")
nbins	the number of bins to use in generating the histograms (default = 100)
legend.position	the position of the legend
legend.justification	the justification of the legend
legend.text.size	the size of the legend labels
title.text.size	the size of the plot title
axis.text.size	the size of the axes text (tick labels)
axis.title.size	the size of the axes titles

Value

A ggplot2-package object.

References

Please see the references for plot_cdf.

Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.

See Also

ggplot2-package, geom_histogram

Examples

## Not run: 
# Logistic Distribution: mean = 0, variance = 1

seed = 1234

# Simulate "external" data set
set.seed(seed)
ext_y <- rlogis(10000)

# Find standardized cumulants
stcum <- calc_theory(Dist = "Logistic", params = c(0, 1))

# Simulate without the sixth cumulant correction
# (invalid power method pdf)
Logvar1 <- nonnormvar1(method = "Polynomial", means = 0, vars = 1,
                      skews = stcum[3], skurts = stcum[4],
                      fifths = stcum[5], sixths = stcum[6],
                      n = 10000, seed = seed)

# Plot simulated variable and external data
plot_sim_ext(sim_y = Logvar1$continuous_variable,
             title = "Invalid Logistic Simulated Data Values",
             ext_y = ext_y)

# Simulate with the sixth cumulant correction
# (valid power method pdf)
Logvar2 <- nonnormvar1(method = "Polynomial", means = 0, vars = 1,
                      skews = stcum[3], skurts = stcum[4],
                      fifths = stcum[5], sixths = stcum[6],
                      Six = seq(1.5, 2, 0.05), n = 10000, seed = seed)

# Plot simulated variable and external data
plot_sim_ext(sim_y = Logvar2$continuous_variable,
             title = "Valid Logistic Simulated Data Values",
             ext_y = ext_y)

# Simulate 2 Poisson distributions (means = 10, 15) and correlation 0.3
# using Method 1
Pvars <- rcorrvar(k_pois = 2, lam = c(10, 15),
                  rho = matrix(c(1, 0.3, 0.3, 1), 2, 2), seed = seed)

# Simulate "external" data set
set.seed(seed)
ext_y <- rpois(10000, 10)

# Plot 1st simulated variable and external data
plot_sim_ext(sim_y = Pvars$Poisson_variable[, 1], ext_y = ext_y)


## End(Not run)

SimMultiCorrData documentation built on May 2, 2019, 9:50 a.m.