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Type 'q()' to quit R. > > > library(DescTools) > > # stopifnot(exprs = { > # all.equal(pretty10exp(10^expo, drop.1=TRUE, sub10 = c(-2, 2)), > # expression(10^-3, 0.01, 0.1, 1, 10, 100, 10^3, 10^4)) > # > # identical(pretty10exp(10^expo, drop.1=TRUE, sub10 = c(-2, 2), lab.type="latex"), > # c("$10^{-3}$", "0.01", "0.1", "1", "10", "100", > # "$10^{3}$", "$10^{4}$")) > # ## gave exponential format for "latex" case. > # }) > # > > set.seed(45) > (z <- as.numeric(names(w <- table(x <- sample(-10:20, size=50, r=TRUE))))) [1] -9 -8 -7 -6 -5 -4 -3 -2 0 3 4 5 6 7 8 9 10 12 13 15 16 17 18 19 20 > > stopifnot(all( + identical(Mode(5), structure(NA_real_, freq = NA_integer_)) + , identical(Mode(NA), structure(NA_real_, freq = NA_integer_)) + , identical(Mode(c(NA, NA)), structure(NA_real_, freq = NA_integer_)) + , identical(Mode(c(NA, 0:5)), structure(NA_real_, freq = NA_integer_)) + , identical(Mode(c(NA, 0:5), na.rm=TRUE), structure(NA_real_, freq = NA_integer_)) + , identical(Mode(c(NA, 0:5, 5), na.rm=TRUE), structure(5, freq = 2L)) + , identical(Mode(c(0:5, 4, 5, 6)), structure(c(4, 5), freq = 2L)) + , identical(Mode(c(0:8, rep(c(1,3, 8), each=5))), structure(c(1, 3, 8), freq = 6L)) + + , all.equal(Kurt(x = z, weights = w, method = 1), Kurt(x = x, method = 1)) + , all.equal(Kurt(x = z, weights = w, method = 2), Kurt(x = x, method = 2)) + , all.equal(Kurt(x = z, weights = w, method = 3), Kurt(x = x, method = 3)) + + , all.equal(Skew(x = z, weights = w, method = 1), Skew(x = x, method = 1)) + , all.equal(Skew(x = z, weights = w, method = 2), Skew(x = x, method = 2)) + , all.equal(Skew(x = z, weights = w, method = 3), Skew(x = x, method = 3)) + + , all.equal(CoefVar(z, weights = w, unbiased = TRUE), CoefVar(x, unbiased = TRUE)) + , all.equal(CoefVar(z, weights = w, unbiased = FALSE), CoefVar(x, unbiased = FALSE)) + + , all.equal(MeanAD(x), MeanAD(z, w)) + , all.equal(MeanAD(x, center = Median), MeanAD(z, w, center = Median)) + , all.equal(MeanAD(x, center = 7), MeanAD(z, w, center = 7)) + + )) > > > > # test Desc base function > > x <- c(rnorm(n = 100, sd = 10), NA) > z <- Desc(x)[[1]] > > stopifnot(all( + identical(z$length, length(x)) + , identical(z$NAs, sum(is.na(x))) + , identical(z$unique, length(unique(na.omit(x)))) + , identical(z$`0s`, sum(x==0, na.rm=TRUE)) + , IsZero(z$mean - mean(x, na.rm=TRUE)) + , identical(unname(z$quant), + unname(quantile(x, na.rm=TRUE, probs=c(0,0.05,.1,.25,.5,.75,.9,.95,1)))) + , identical(z$range, diff(range(x, na.rm=TRUE))) + , IsZero(z$sd - sd(x, na.rm=TRUE)) + , IsZero(z$vcoef - sd(x, na.rm=TRUE)/mean(x, na.rm = TRUE)) + , identical(z$mad, mad(x, na.rm=TRUE)) + , identical(z$IQR, IQR(x, na.rm=TRUE)) + )) > > > > > # test BinomDiffCI with https://www.lexjansen.com/wuss/2016/127_Final_Paper_PDF.pdf > > # 5. Mee is given as 0.0533 in the literature, which probably is a rounding error > # it's corrected from 0.533 to 0.534 in ‘lit1’ and from 0.7225 to 0.7224 in ‘lit2’ for comparison reasons > # Mee 4 from 0.0857 to 0.0858 > > meth <- c("wald","waldcc","hal","jp","mee","mn","score","scorecc","ha","ac","blj") > > # use all(IsZero(x - y)) to take into account numerical properties of > # certain operating systems (especially PowerPC) > stopifnot(all( + all(IsZero(unname(round(BinomDiffCI(56, 70, 48, 80, method = meth), 4)[, -1]) - + cbind(c(0.0575, 0.0441, 0.0535, 0.0531, 0.0534, + 0.0528, 0.0524, 0.0428, 0.0494, 0.0525, 0.054), + c(0.3425, 0.3559, 0.3351, 0.3355, 0.3377, + 0.3382, 0.3339, 0.3422, 0.3506, 0.3358, 0.34)))), + all(IsZero(unname(round(BinomDiffCI(9, 10, 3, 10, method = meth), 4)[, -1]) - + cbind(c(0.2605, 0.1605, 0.1777, 0.176, 0.1821, + 0.17, 0.1705, 0.1013, 0.1922, 0.16, 0.1869), + c(0.9395, 1, 0.8289, 0.8306, 0.837, 0.8406, + 0.809, 0.8387, 1, 0.84, 0.904)))), + all(IsZero(unname(round(BinomDiffCI(10, 10, 0, 20, method = meth), 4)[, -1]) - + cbind(c(1, 0.925, 0.7482, 0.7431, 0.7224, 0.7156, + 0.6791, 0.6014, 0.95, 0.6922, 0.7854), + c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)))), + all(IsZero(unname(round(BinomDiffCI(84, 101, 89, 105, method = meth), 4)[, -1]) - + cbind(c(-0.1162, -0.1259, -0.1152, -0.116, -0.1188, + -0.1191, -0.1177, -0.1245, -0.1216, -0.1168, -0.117), + c(0.0843, 0.094, 0.0834, 0.0843, 0.0858, 0.086, 0.0851, + 0.0918, 0.0898, 0.085, 0.0852)))) + )) > > > > # test for median, calculated by Quantile > x <- sample(19, 30, replace = TRUE) > z <- as.numeric(names(w <- table(x))) > stopifnot(AllIdentical(Median(z, weights=w), Median(x), median(x), Median(c(x, NA, NA), na.rm=TRUE))) > > x <- sample(40, 30, replace = TRUE) > z <- as.numeric(names(w <- table(x))) > stopifnot(AllIdentical(Median(z, weights=w), Median(x), median(x), Median(c(x, NA, NA), na.rm=TRUE))) > > x <- runif(40) > z <- as.numeric(names(w <- table(x))) > stopifnot(AllIdentical(Median(z, weights=w), Median(x), median(x), Median(c(x, NA, NA), na.rm=TRUE))) > > > ## LogStInv() was wrong for base != 10 > x <- seq(0, 10, by=1/4) > tx <- LogSt(x, base=2, threshold=6) > x. <- LogStInv(tx) > all.equal(x, x., tol = 0) # gave 0.15144. before bug fix [1] "Mean relative difference: 1.528616e-16" > stopifnot(all.equal(x, x., tol = 1e-14)) > > > # Test for correct using of weights in .NormWeights() and Mean() > stopifnot(AllIdentical( + Mean(x=c(0,2,4,6)) + , Mean(x=c(0,2,4,6), na.rm=TRUE) + , Mean(x=c(0,2,4,6), zero.rm=TRUE) + , Mean(x=c(0,2,4,6), weights = rep(1, 4), zero.rm=TRUE) + , Mean(x=c(0,2,4,6), weights = rep(1, 4), na.rm=TRUE, zero.rm=TRUE) + )) > > > stopifnot(IsZero(DescTools::HodgesLehmann(c(0.7,0.5,0.5)) - 0.55)) > > stopifnot(IsZero( + HodgesLehmann(c(50.6, 39.2, 35.2, 17, 11.2, 14.2, 24.2, 37.4, 35.2), + c(38, 18.6, 23.2, 19, 6.6, 16.4, 14.4, 37.6, 24.4) ) - 7.8)) > > > > > proc.time() user system elapsed 1.45 0.32 1.76