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#' Gaussian Process Approximations for Designing Experiment
#'
#' The \code{GADGET} package computes near-optimal Bayesian experimental designs using Gaussian process optimization. At its core is the ability to calculate static designs that maximize a design criterion that may be either deterministic or stochastic. In particular, stochastic design criteria could be a Monte Carlo estimator of an expected utility based on MCMC posterior draws. \code{GADGET} utilizes the algorithm proposed by Weaver et al. (2016) <doi:10.1214/15-BA945> and performs Gaussian process validation using the statistics introduced by Bastos and O’Hagan (2009) <doi:10.1198/TECH.2009.08019>. The \code{pbapply} package is integrated to parallelize the evaluation of the user's design criterion. Additionally, \code{GADGET} has wrapped the optimization into a sequential routine to perform sequential computer experiments that automatically call simulator code that is available in R.
#'
#' @references Weaver, B. P., Williams, B. J., Anderson-Cook, C. M., Higdon, D. M. (2016). Computational enhancements to Bayesian design of experiments using Gaussian processes. Bayesian Analysis, 11(1), 191–213, <doi:10.1214/15-BA945>.
#'
#' @docType package
#' @author Isaac Michaud, Brian Weaver, and Brian Williams
#' @name GADGET
NULL
#' Print ASCII GADGET Logo
#'
#' Prints the GADGET ASCII logo in the center of the console.
#'
#' @return Nothing
#' @keywords internal
#' @export
#' @examples
#' print_logo()
print_logo <- function() {
logo <- list()
logo[[1]] <- " ____ _ ____ ____ _____ _____\n "
#logo[[2]] <- "/ ___| / \\ | \\ / ___| ____|_ _|\n"
logo[[2]] <- "/ ___| / \\ | _ \\ / ___| ____|_ _|\n"
#logo[[3]] <- "| | _ / _ \\ | |\U203E| | | _| _| | | \n"
logo[[3]] <- "| | _ / _ \\ | | | | | _| _| | | \n"
logo[[4]] <- "| |_| |/ ___ \\| |_| | |_| | |___ | |\n"
logo[[5]] <- " \\____/_/ \\_\\____/ \\____|_____| |_|\n"
subtitle <- "Gaussian Process Approximations for Designing Experiments\n"
width <- getOption("width")
ws <- rep(" ", floor((width - nchar(logo[[1]]))/2))
for (i in 1:5){
cat(ws,logo[[i]],sep = "")
}
cat(rep("-",width),'\n',sep = "")
ws <- rep(" ", floor((width - nchar(subtitle))/2))
cat(ws,subtitle,sep="")
}
#' Print Separator
#'
#' Prints a string of dashes to separate output.
#'
#' @return Nothing
#' @keywords internal
#' @export
#' @examples
#' print_separate()
print_separate <-function() {
width <- getOption("width")
cat(rep("-",width),'\n',sep = "")
}
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