version 1.0.0

DESCRIPTION

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+Package: groupTesting
+Title: Simulating and Modeling Group (Pooled) Testing Data
+Version: 1.0.0
+Date: 2021-11-19
+Author: Md S. Warasi
+Maintainer: Md S. Warasi <msarker@radford.edu>
+Description: Provides an expectation-maximization (EM) algorithm using the approach introduced in Xie (2001) <doi:10.1002/sim.817>. The EM algorithm can be used to estimate the prevalence (overall proportion) of a disease and to estimate a binary regression model from among the class of generalized linear models based on group testing data. The estimation framework we consider offers a flexible and general approach; i.e., its application is not limited to any specific group testing protocol. Consequently, the EM algorithm can model data arising from simple pooling as well as advanced pooling such as hierarchical testing, array testing, and quality control pooling. Also, provided are functions that can be used to conduct the Wald tests described in Buse (1982) <doi:10.1080/00031305.1982.10482817> and to simulate the group testing data described in Kim et al. (2007) <doi:10.1111/j.1541-0420.2007.00817.x>.
+License: GPL-3
+Depends: R(>= 3.5.0)
+Imports: pracma
+NeedsCompilation: yes
+Encoding: UTF-8
+RoxygenNote: 7.1.1
+Packaged: 2021-11-19 18:49:25 UTC; msarker
+Repository: CRAN
+Date/Publication: 2021-11-22 09:00:02 UTC

MD5

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+2d2e7f5417633fc3e05179f24ce12867 *DESCRIPTION
+19e4497639be28ffc4dc737e66e5e2d7 *NAMESPACE
+67e9f5c036f34456c44ea590b83e93b2 *R/gtcode.R
+e7110e7f48030f35698eb91d91a4e528 *R/linkfns.R
+a449c57bfef435657267f231eba233ca *R/propEM.R
+b6523d7dfb32c95639cced2d36b2c0fc *R/regEM.R
+c0f4895459d8677dec2f2ad4600141f0 *R/waldTest.R
+e30b5e61eb92e83201c46850741bfaec *man/array.gt.simulation.Rd
+153f56fbddfd60e6bf7ac2fdd424b0c5 *man/glm.gt.Rd
+005753654cb1ba175c4a66d57e5d166e *man/glmLink.Rd
+98cd54c4cb84265e55b4bb7c982cf39e *man/hier.gt.simulation.Rd
+2140f47f6eaa073f0b042aad9ed5da82 *man/prop.gt.Rd
+148ef1e8336716c9208b7e77ad53fbef *man/waldTest.Rd
+9b11ec0e9f983e39a5cf915d5002dc6f *src/Makevars.txt
+cb44d44d2eb4d6b7ffd7d32607f5968e *src/gtestingc.c
+1f0efc225a8218d7aad4216e8597ab7a *src/gtestingf.f95

NAMESPACE

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+# Generated by roxygen2: do not edit by hand
+
+export(array.gt.simulation)
+export(glm.gt)
+export(glmLink)
+export(hier.gt.simulation)
+export(prop.gt)
+export(waldTest)
+importFrom(pracma,fderiv)
+importFrom(stats,optim)
+importFrom(stats,pchisq)
+importFrom(stats,pnorm)
+importFrom(stats,qnorm)
+importFrom(stats,rbinom)
+importFrom(stats,runif)
+useDynLib(groupTesting, .registration=TRUE)

R/linkfns.R

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+#' Link Functions in the Class of Generalized Linear Models
+#'
+#' This function provides characteristics of common link functions (logit, probit, and comlementary log-log). Specifically, based on the link name, the function with its inverse, first derivative, and second derivative is provided. 
+#'
+#' @param fn.name One of the three: "logit", "probit", and "cloglog".
+#'
+#' @importFrom stats pnorm
+#' @importFrom stats qnorm
+#'
+#' @return A list with components:
+#' \item{g}{The link function corresponding to "logit", "probit", or "cloglog".}
+#' \item{dg}{The first derivative of g.}
+#' \item{d2g}{The second derivative of g.}
+#' \item{gInv}{The inverse of g.}
+#' 
+#' @export
+#' 
+#' @examples
+#' ## Try:
+#' glmLink("logit")
+#' 
+glmLink <- function(fn.name=c("logit","probit","cloglog")){
+  fn.name <- match.arg(fn.name)
+
+  # Logit link
+  if(fn.name == "logit"){
+    g <- function(u){exp(u)/(1+exp(u))}
+    dg <- function(u){exp(u)/(1+exp(u))^2}
+    d2g <- function(u){exp(u)*(1-exp(u))/(1+exp(u))^3}
+    g.inv <- function(u){log(u/(1-u))}
+  }
+  # Probit link
+  if(fn.name == "probit"){
+    g <- function(u){stats::pnorm(u)}
+    dg <- function(u){exp(-u^2/2)/sqrt(2*pi)}
+    d2g <- function(u){-u*exp(-u^2/2)/sqrt(2*pi)}
+    g.inv <- function(u){stats::qnorm(u)}
+  }
+  # Complementary log-log link
+  if(fn.name == "cloglog"){
+    g <- function(u){1 - exp(-exp(u))}
+    dg <- function(u){exp(u)*exp(-exp(u))}
+    d2g <- function(u){exp(u)*exp(-exp(u))*(1-exp(u))}
+    g.inv <- function(u){log(-log(1-u))}
+  }
+  list("g"   = g,
+       "dg"  = dg,
+       "d2g" = d2g,
+       "gInv"= g.inv)
+}