update packages R 3.6.3

BiasedUrn/DESCRIPTION

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+Package: BiasedUrn
+Type: Package
+Title: Biased Urn Model Distributions
+Version: 1.07
+Date: 2015-12-28
+Author: Agner Fog
+Maintainer: Agner Fog <agner@agner.org>
+Description: Statistical models of biased sampling in the form of 
+  univariate and multivariate noncentral hypergeometric distributions, 
+  including Wallenius' noncentral hypergeometric distribution and
+  Fisher's noncentral hypergeometric distribution 
+  (also called extended hypergeometric distribution).  
+  See vignette("UrnTheory") for explanation of these distributions.
+License: GPL-3
+URL: http://www.agner.org/random/ http://www.r-project.org
+Packaged: 2015-12-28 07:10:49 UTC; A
+NeedsCompilation: yes
+Repository: CRAN
+Date/Publication: 2015-12-28 09:01:09
+Built: R 3.6.3; x86_64-pc-linux-gnu; 2020-09-23 19:35:30 UTC; unix

BiasedUrn/INDEX

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+BiasedUrn               Biased Urn Model Distributions
+BiasedUrn-Multivariate
+                        Biased urn models: Multivariate distributions
+BiasedUrn-Univariate    Biased urn models: Univariate distributions

BiasedUrn/NAMESPACE

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+useDynLib(BiasedUrn)
+
+# Functions in urn1.R
+export(dFNCHypergeo)
+export(dWNCHypergeo)
+export(pFNCHypergeo)
+export(pWNCHypergeo)
+export(qFNCHypergeo)
+export(qWNCHypergeo)
+export(rFNCHypergeo)
+export(rWNCHypergeo)
+export(meanFNCHypergeo)
+export(meanWNCHypergeo)
+export(varFNCHypergeo)
+export(varWNCHypergeo)
+export(modeFNCHypergeo)
+export(modeWNCHypergeo)
+export(oddsFNCHypergeo)
+export(oddsWNCHypergeo)
+export(numFNCHypergeo)
+export(numWNCHypergeo)
+export(minHypergeo)
+export(maxHypergeo)
+
+# Functions in urn2.R
+export(dMFNCHypergeo)
+export(dMWNCHypergeo)
+export(rMFNCHypergeo)
+export(rMWNCHypergeo)
+export(momentsMFNCHypergeo)
+export(momentsMWNCHypergeo)
+export(meanMFNCHypergeo)
+export(meanMWNCHypergeo)
+export(varMFNCHypergeo)
+export(varMWNCHypergeo)
+export(oddsMFNCHypergeo)
+export(oddsMWNCHypergeo)
+export(numMFNCHypergeo)
+export(numMWNCHypergeo)
+export(minMHypergeo)
+export(maxMHypergeo)

BiasedUrn/R/BiasedUrn

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+#  File share/R/nspackloader.R
+#  Part of the R package, http://www.R-project.org
+#
+#  Copyright (C) 1995-2012 The R Core Team
+#
+#  This program is free software; you can redistribute it and/or modify
+#  it under the terms of the GNU General Public License as published by
+#  the Free Software Foundation; either version 2 of the License, or
+#  (at your option) any later version.
+#
+#  This program is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#  GNU General Public License for more details.
+#
+#  A copy of the GNU General Public License is available at
+#  http://www.r-project.org/Licenses/
+
+local({
+    info <- loadingNamespaceInfo()
+    pkg <- info$pkgname
+    ns <- .getNamespace(as.name(pkg))
+    if (is.null(ns))
+        stop("cannot find namespace environment for ", pkg, domain = NA);
+    dbbase <- file.path(info$libname, pkg, "R", pkg)
+    lazyLoad(dbbase, ns, filter = function(n) n != ".__NAMESPACE__.")
+})

BiasedUrn/demo/ApproxHypergeo.R

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+# ApproxHypergeo.R
+# This demo compares a Wallenius' and a Fisher's noncentral hypergeometric 
+# distribution with the same mean rather than the same odds in order to
+# make them approximate each other better.
+
+require(BiasedUrn)
+require(stats)
+
+ApproxHypPlot <- function(m1, m2, n, w.odds) {
+  xmin <- minHypergeo(m1, m2, n)
+  xmax <- maxHypergeo(m1, m2, n)
+  x <- xmin : xmax
+  w.mean <- meanWNCHypergeo(m1, m2, n, w.odds)
+  f.odds <- oddsFNCHypergeo(w.mean, m1, m2, n)
+  wnc  <- dWNCHypergeo(x, m1, m2, n, w.odds)
+  fnc  <- dFNCHypergeo(x, m1, m2, n, f.odds)
+  fnc0 <- dFNCHypergeo(x, m1, m2, n, w.odds)
+  plot   (x, fnc, type="l", col="red",
+     main = "Hypergeometric distributions",
+     sub = "Blue = Wallenius, Red = Fisher w. same mean,\n Green = Fisher w. same odds",
+     xlab = "", ylab = "Probability")
+  points (x, wnc, type="l", col="blue")
+  points (x, fnc0, type="l", col="green", lty="dashed")
+}
+
+ApproxHypPlot(80, 60, 100, 0.5)

BiasedUrn/demo/CompareHypergeo.R

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+# CompareHypergeo.R
+# This demo shows the difference between the three distributions:
+# 1. Wallenius' noncentral hypergeometric distribution
+# 2. Fisher's noncentral hypergeometric distribution
+# 3. The (central) hypergeometric distribution
+
+require(BiasedUrn)
+require(stats)
+
+ComparePlot <- function(m1, m2, n, odds) {
+  xmin <- minHypergeo(m1, m2, n)
+  xmax <- maxHypergeo(m1, m2, n)
+  x <- xmin : xmax
+  wnc <- dWNCHypergeo(x, m1, m2, n, odds)
+  fnc <- dFNCHypergeo(x, m1, m2, n, odds)
+  hyp <- dhyper(x, m1, m2, n)
+  plot   (x, wnc, type="l", col="blue", 
+     main = "Hypergeometric distributions", 
+     sub = "Blue = Wallenius, Red = Fisher, Green = Central",
+     xlab = "x", ylab = "Probability")
+  points (x, fnc, type="l", col="red")
+  points (x, hyp, type="l", col="green")
+}
+
+ComparePlot(80, 60, 100, 0.5)

BiasedUrn/demo/OddsPrecision.R

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+# OddsPrecision.R
+# This demo tests the precision of the odds functions for
+# Wallenius' and a Fisher's noncentral hypergeometric distributions
+# by calculating the mean of distributions with known odds and then 
+# estimating the odds from the means.
+
+require(BiasedUrn)
+require(stats)
+
+OddsEst <- function(m1, m2, n, odds) {
+   meanW <- meanWNCHypergeo(m1, m2, n, odds, 1E-9)
+   oddsEstW <- oddsWNCHypergeo(meanW, m1, m2, n)
+   meanF <- meanFNCHypergeo(m1, m2, n, odds, 1E-9)
+   oddsEstF <- oddsFNCHypergeo(meanF, m1, m2, n)
+   list(Odds=odds, Wallenius.mean = meanW, Fisher.mean = meanF,
+   Wallenius.estimated.odds = oddsEstW, Fisher.estimated.odds = oddsEstF, 
+   Wallenius.rel.error = (oddsEstW-odds)/odds, 
+   Fisher.rel.error = (oddsEstF-odds)/odds)
+}
+
+OddsEst(10, 12, 15, 0.6)

BiasedUrn/demo/SampleWallenius.R

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+# SampleWallenius.R
+# This demo makes random samples from Wallenius' noncentral hypergeometric 
+# distribution and compares measured and expected frequencies
+
+require(BiasedUrn)
+require(stats)
+
+MakeSamples <- function(m1, m2, n, odds) {
+  nsamp <- 100000                  # Desired number of samples from distribution
+  xmin  <- minHypergeo(m1, m2, n)  # Lower limit for x
+  xmax  <- maxHypergeo(m1, m2, n)  # Upper limit for x
+
+  # Make nsamp samples from Wallenius' distribution
+  X <- rWNCHypergeo(nsamp, m1, m2, n, odds)
+
+  # Get table of frequencies
+  XTab <- as.data.frame(table(X))
+
+  # Relative frequencies
+  XTab$Freq <- XTab$Freq / nsamp
+
+  # Get expected frequencies
+  XTab$Expected <- dWNCHypergeo(as.integer(levels(XTab$X)), m1, m2, n, odds)
+
+  print("X frequencies in Wallenius' noncentral hypergeometric distribution")
+
+  # List measured vs. expected frequencies
+  # (How do I get rid of the row names?)
+  print(XTab, digits=5)
+
+  # Draw histogram
+  # (Why does my histogram show densities bigger than 1?)
+  hist(X, freq=FALSE)
+}
+
+MakeSamples(6, 8, 5, 1.5)

BiasedUrn/demo/UrnTheory.R

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+# UrnTheory.R
+# This opens the file UrnTheory.pdf to explain the biased urn models.
+
+vignette("UrnTheory", package="BiasedUrn")