packrat/lib/x86_64-w64-mingw32/3.4.3/Rcpp/unitTests/runit.stats.R

#!/usr/bin/env r
# -*- mode: R; tab-width: 4; -*-
#
# Copyright (C) 2010 - 2013  Dirk Eddelbuettel and Romain Francois
#
# This file is part of Rcpp.
#
# Rcpp 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.
#
# Rcpp 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.
#
# You should have received a copy of the GNU General Public License
# along with Rcpp.  If not, see <http://www.gnu.org/licenses/>.

.runThisTest <- Sys.getenv("RunAllRcppTests") == "yes"

if (.runThisTest) {

    .setUp <- Rcpp:::unitTestSetup("stats.cpp")

    test.stats.dbeta <- function() {
        vv <- seq(0, 1, by = 0.1)
        a <- 0.5; b <- 2.5
        checkEquals(runit_dbeta(vv, a, b),
                    list(
                        NoLog = dbeta(vv, a, b),
                        Log   = dbeta(vv, a, b, log=TRUE)
                        ),
                    msg = " stats.qbeta")
    }

    test.stats.dbinom <- function( ){
        v <- 1:10
        checkEquals(runit_dbinom(v) ,
                    list(
                        false = dbinom(v, 10, .5),
                        true = dbinom(v, 10, .5, TRUE )
                        ), msg = "stats.dbinom" )
    }

    test.stats.dunif <- function() {
        vv <- seq(0, 1, by = 0.1)
        checkEquals(runit_dunif(vv),
                    list(
                        NoLog_noMin_noMax = dunif(vv),
                        NoLog_noMax = dunif(vv, 0),
                        NoLog = dunif(vv, 0, 1),
                        Log   = dunif(vv, 0, 1, log=TRUE),
                        Log_noMax   = dunif(vv, 0, log=TRUE)
                                        #,Log_noMin_noMax   = dunif(vv, log=TRUE)  ## wrong answer
                        ),
                    msg = " stats.dunif")
    }

    test.stats.dgamma <- function( ) {
        v <- 1:4
        checkEquals(runit_dgamma(v),
                    list( NoLog = dgamma(v, 1.0, 1.0),
                         Log = dgamma(v, 1.0, 1.0, log = TRUE ),
                         Log_noRate = dgamma(v, 1.0, log = TRUE )
                         ), msg = "stats.dgamma" )
    }


    test.stats.dpois <- function( ){
        v <- 0:5
        checkEquals(runit_dpois(v) ,
                    list( false = dpois(v, .5),
                         true = dpois(v, .5, TRUE )
                         ), msg = "stats.dpois" )
    }

    test.stats.dnorm <- function( ) {
        v <- seq(0.0, 1.0, by=0.1)
        checkEquals(runit_dnorm(v),
                    list( false_noMean_noSd = dnorm(v),
                         false_noSd = dnorm(v, 0.0),
                         false = dnorm(v, 0.0, 1.0),
                         true = dnorm(v, 0.0, 1.0, log=TRUE ),
                         true_noSd = dnorm(v, 0.0, log=TRUE ),
                         true_noMean_noSd = dnorm(v, log=TRUE )
                         ), msg = "stats.dnorm" )
    }

    test.stats.dt <- function( ) {
        v <- seq(0.0, 1.0, by=0.1)
        checkEquals(runit_dt(v),
                    list( false = dt(v, 5),
                         true = dt(v, 5, log=TRUE ) # NB: need log=TRUE here
                         ), msg = "stats.dt" )
    }

    test.stats.pbeta <- function( ) {
        a <- 0.5; b <- 2.5
        v <- qbeta(seq(0.0, 1.0, by=0.1), a, b)
        checkEquals(runit_pbeta(v, a, b),
                    list(lowerNoLog = pbeta(v, a, b),
                         lowerLog   = pbeta(v, a, b,              log=TRUE),
                         upperNoLog = pbeta(v, a, b, lower=FALSE),
                         upperLog   = pbeta(v, a, b, lower=FALSE, log=TRUE)
                         ),
                    msg = " stats.pbeta" )
        ## Borrowed from R's d-p-q-r-tests.R
        x <- c(.01, .10, .25, .40, .55, .71, .98)
        pbval <- c(-0.04605755624088, -0.3182809860569, -0.7503593555585,
                   -1.241555830932, -1.851527837938, -2.76044482378, -8.149862739881)
        checkEqualsNumeric(runit_pbeta(x, 0.8, 2)$upperLog, pbval, msg = " stats.pbeta")
        checkEqualsNumeric(runit_pbeta(1-x, 2, 0.8)$lowerLog, pbval, msg = " stats.pbeta")
    }

    test.stats.pbinom <- function( ) {
        n <- 20
        p <- 0.5
        vv <- 0:n
        checkEquals(runit_pbinom(vv, n, p),
                    list(lowerNoLog = pbinom(vv, n, p),
                         lowerLog   = pbinom(vv, n, p, log=TRUE),
                         upperNoLog = pbinom(vv, n, p, lower=FALSE),
                         upperLog   = pbinom(vv, n, p, lower=FALSE, log=TRUE)
                         ),
                    msg = " stats.pbinom")
    }

    test.stats.pcauchy <- function( ) {
        location <- 0.5
        scale <- 1.5
        vv <- 1:5
        checkEquals(runit_pcauchy(vv, location, scale),
                    list(lowerNoLog = pcauchy(vv, location, scale),
                         lowerLog   = pcauchy(vv, location, scale, log=TRUE),
                         upperNoLog = pcauchy(vv, location, scale, lower=FALSE),
                         upperLog   = pcauchy(vv, location, scale, lower=FALSE, log=TRUE)
                         ),
                    msg = " stats.pcauchy")
    }

    test.stats.punif <- function( ) {
        v <- qunif(seq(0.0, 1.0, by=0.1))
        checkEquals(runit_punif(v),
                    list(lowerNoLog = punif(v),
                         lowerLog   = punif(v, log=TRUE ),
                         upperNoLog = punif(v, lower=FALSE),
                         upperLog   = punif(v, lower=FALSE, log=TRUE)
                         ),
                    msg = "stats.punif" )
                                        # TODO: also borrow from R's d-p-q-r-tests.R
    }

    test.stats.pf <- function( ) {
        v <- (1:9)/10
        checkEquals(runit_pf(v),
                    list(lowerNoLog = pf(v, 6, 8, lower=TRUE, log=FALSE),
                         lowerLog   = pf(v, 6, 8, log=TRUE ),
                         upperNoLog = pf(v, 6, 8, lower=FALSE),
                         upperLog   = pf(v, 6, 8, lower=FALSE, log=TRUE)
                         ),
                    msg = "stats.pf" )
    }

    test.stats.pnf <- function( ) {
        v <- (1:9)/10
        checkEquals(runit_pnf(v),
                    list(lowerNoLog = pf(v, 6, 8, ncp=2.5, lower=TRUE, log=FALSE),
                         lowerLog   = pf(v, 6, 8, ncp=2.5, log=TRUE ),
                         upperNoLog = pf(v, 6, 8, ncp=2.5, lower=FALSE),
                         upperLog   = pf(v, 6, 8, ncp=2.5, lower=FALSE, log=TRUE)
                         ),
                    msg = "stats.pnf" )
    }

    test.stats.pchisq <- function( ) {
        v <- (1:9)/10
        checkEquals(runit_pchisq(v),
                    list(lowerNoLog = pchisq(v, 6, lower=TRUE, log=FALSE),
                         lowerLog   = pchisq(v, 6, log=TRUE ),
                         upperNoLog = pchisq(v, 6, lower=FALSE),
                         upperLog   = pchisq(v, 6, lower=FALSE, log=TRUE)
                         ),
                    msg = "stats.pchisq" )
    }

    test.stats.pnchisq <- function( ) {
        v <- (1:9)/10
        checkEquals(runit_pnchisq(v),
                    list(lowerNoLog = pchisq(v, 6, ncp=2.5, lower=TRUE, log=FALSE),
                         lowerLog   = pchisq(v, 6, ncp=2.5, log=TRUE ),
                         upperNoLog = pchisq(v, 6, ncp=2.5, lower=FALSE),
                         upperLog   = pchisq(v, 6, ncp=2.5, lower=FALSE, log=TRUE)
                         ),
                    msg = "stats.pnchisq" )
    }

    test.stats.pgamma <- function( ) {
        v <- (1:9)/10
        checkEquals(runit_pgamma(v),
                    list(lowerNoLog = pgamma(v, shape = 2.0),
                         lowerLog   = pgamma(v, shape = 2.0, log=TRUE ),
                         upperNoLog = pgamma(v, shape = 2.0, lower=FALSE),
                         upperLog   = pgamma(v, shape = 2.0, lower=FALSE, log=TRUE)
                         ),
                    msg = "stats.pgamma" )
    }


    test.stats.pnorm <- function( ) {
        v <- qnorm(seq(0.0, 1.0, by=0.1))
        checkEquals(runit_pnorm(v),
                    list(lowerNoLog = pnorm(v),
                         lowerLog   = pnorm(v, log=TRUE ),
                         upperNoLog = pnorm(v, lower=FALSE),
                         upperLog   = pnorm(v, lower=FALSE, log=TRUE)
                         ),
                    msg = "stats.pnorm" )
        ## Borrowed from R's d-p-q-r-tests.R
        z <- c(-Inf,Inf,NA,NaN, rt(1000, df=2))
        z.ok <- z > -37.5 | !is.finite(z)
        pz <- runit_pnorm(z)
        checkEqualsNumeric(pz$lowerNoLog, 1 - pz$upperNoLog, msg = "stats.pnorm")
        checkEqualsNumeric(pz$lowerNoLog, runit_pnorm(-z)$upperNoLog, msg = "stats.pnorm")
        checkEqualsNumeric(log(pz$lowerNoLog[z.ok]), pz$lowerLog[z.ok], msg = "stats.pnorm")
        ## FIXME: Add tests that use non-default mu and sigma
    }

    test.stats.ppois <- function( ) {
        vv <- 0:20
        checkEquals(runit_ppois(vv),
                    list(lowerNoLog = ppois(vv, 0.5),
                         lowerLog   = ppois(vv, 0.5,              log=TRUE),
                         upperNoLog = ppois(vv, 0.5, lower=FALSE),
                         upperLog   = ppois(vv, 0.5, lower=FALSE, log=TRUE)
                         ),
                    msg = " stats.ppois")
    }

    test.stats.pt <- function( ) {
        v <- seq(0.0, 1.0, by=0.1)
        checkEquals(runit_pt(v),
                    list(lowerNoLog = pt(v, 5),
                         lowerLog   = pt(v, 5,              log=TRUE),
                         upperNoLog = pt(v, 5, lower=FALSE),
                         upperLog   = pt(v, 5, lower=FALSE, log=TRUE) ),
                    msg = "stats.pt" )
    }

    test.stats.pnt <- function( ) {
        v <- seq(0.0, 1.0, by=0.1)
        checkEquals(runit_pnt(v),
                    list(lowerNoLog = pt(v, 5, ncp=7),
                         lowerLog   = pt(v, 5, ncp=7,              log=TRUE),
                         upperNoLog = pt(v, 5, ncp=7, lower=FALSE),
                         upperLog   = pt(v, 5, ncp=7, lower=FALSE, log=TRUE) ),
                    msg = "stats.pnt" )
    }

    test.stats.qbinom <- function( ) {
        n <- 20
        p <- 0.5
        vv <- seq(0, 1, by = 0.1)
        checkEquals(runit_qbinom_prob(vv, n, p),
                    list(lower = qbinom(vv, n, p),
                         upper = qbinom(vv, n, p, lower=FALSE)
                         ),
                    msg = " stats.qbinom")
    }

    test.stats.qunif <- function( ) {
        checkEquals(runit_qunif_prob(c(0, 1, 1.1, -.1)),
                    list(lower = c(0, 1, NaN, NaN),
                         upper = c(1, 0, NaN, NaN)
                         ),
                    msg = "stats.qunif" )
                                        # TODO: also borrow from R's d-p-q-r-tests.R
    }

    test.stats.qnorm <- function( ) {
        checkEquals(runit_qnorm_prob(c(0, 1, 1.1, -.1)),
                    list(lower = c(-Inf, Inf, NaN, NaN),
                         upper = c(Inf, -Inf, NaN, NaN)
                         ),
                    msg = "stats.qnorm" )
        ## Borrowed from R's d-p-q-r-tests.R and Wichura (1988)
        checkEqualsNumeric(runit_qnorm_prob(c( 0.25,  .001,	 1e-20))$lower,
                           c(-0.6744897501960817, -3.090232306167814, -9.262340089798408),
                           msg = "stats.qnorm",
                           tol = 1e-15)

        checkEquals(runit_qnorm_log(c(-Inf, 0, 0.1)),
                    list(lower = c(-Inf, Inf, NaN),
                         upper = c(Inf, -Inf, NaN)
                         ),
                    msg = "stats.qnorm" )
        checkEqualsNumeric(runit_qnorm_log(-1e5)$lower, -447.1974945)
    }

    test.stats.qpois.prob <- function( ) {
        vv <- seq(0, 1, by = 0.1)
        checkEquals(runit_qpois_prob(vv),
                    list(lower = qpois(vv, 0.5),
                         upper = qpois(vv, 0.5, lower=FALSE)
                         ),
                    msg = " stats.qpois.prob")
    }

    test.stats.qt <- function( ) {
        v <- seq(0.05, 0.95, by=0.05)
        ( x1 <- runit_qt(v, 5, FALSE, FALSE) )
        ( x2 <- qt(v, df=5, lower=FALSE, log=FALSE) )
        checkEquals(x1, x2, msg="stats.qt.f.f")

        ( x1 <- runit_qt(v, 5, TRUE, FALSE) )
        ( x2 <- qt(v, df=5, lower=TRUE, log=FALSE) )
        checkEquals(x1, x2, msg="stats.qt.t.f")

        ( x1 <- runit_qt(-v, 5, FALSE, TRUE) )
        ( x2 <- qt(-v, df=5, lower=FALSE, log=TRUE) )
        checkEquals(x1, x2, msg="stats.qt.f.t")

        ( x1 <- runit_qt(-v, 5, TRUE, TRUE) )
        ( x2 <- qt(-v, df=5, lower=TRUE, log=TRUE) )
        checkEquals(x1, x2, msg="stats.qt.t.t")

    }

    ## TODO: test.stats.qgamma
    ## TODO: test.stats.(dq)chisq

}
UBC-MDS/Karl documentation built on May 22, 2019, 1:53 p.m.