CRAN Package Check Results for Package Formula

Last updated on 2024-03-28 23:01:44 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2-5 1.75 38.26 40.01 OK
r-devel-linux-x86_64-debian-gcc 1.2-5 1.92 30.35 32.27 OK
r-devel-linux-x86_64-fedora-clang 1.2-5 52.42 OK
r-devel-linux-x86_64-fedora-gcc 1.2-5 63.33 OK
r-devel-windows-x86_64 1.2-5 4.00 242.00 246.00 ERROR
r-patched-linux-x86_64 1.2-5 2.14 36.36 38.50 OK
r-release-linux-x86_64 1.2-5 2.47 37.16 39.63 OK
r-release-macos-arm64 1.2-5 35.00 OK
r-release-macos-x86_64 1.2-5 40.00 OK
r-release-windows-x86_64 1.2-5 4.00 69.00 73.00 OK
r-oldrel-macos-arm64 1.2-5 24.00 OK
r-oldrel-windows-x86_64 1.2-5 16.00 115.00 131.00 OK

Check Details

Version: 1.2-5
Check: running R code from vignettes
Result: ERROR Errors in running code in vignettes: when running code in 'Formula.Rnw' > options(width = 70, prompt = "R> ", continue = "+ ") > library("Formula") > set.seed(1090) > dat <- as.data.frame(matrix(round(runif(21), digits = 2), + ncol = 7)) > colnames(dat) <- c("y1", "y2", "y3", "x1", "x2", "x3", + "x4") > for (i in c(2, 6:7)) dat[[i]] <- factor(dat[[i]] < + 0.5, labels = c("a", "b")) > dat$y2[1] <- NA > dat y1 y2 y3 x1 x2 x3 x4 1 0.82 <NA> 0.27 0.09 0.22 a b 2 0.70 a 0.17 0.26 0.46 b b 3 0.65 b 0.28 0.03 0.37 a a > F1 <- Formula(log(y1) ~ x1 + x2 | I(x1^2)) > length(F1) [1] 1 2 > mf1 <- model.frame(F1, data = dat) > mf1 log(y1) x1 x2 I(x1^2) 1 -0.1984509 0.09 0.22 0.0081 2 -0.3566749 0.26 0.46 0.0676 3 -0.4307829 0.03 0.37 9e-04 > model.response(mf1) 1 2 3 -0.1984509 -0.3566749 -0.4307829 > model.matrix(F1, data = mf1, rhs = 1) (Intercept) x1 x2 1 1 0.09 0.22 2 1 0.26 0.46 3 1 0.03 0.37 attr(,"assign") [1] 0 1 2 > model.matrix(F1, data = mf1, rhs = 2) (Intercept) I(x1^2) 1 1 0.0081 2 1 0.0676 3 1 0.0009 attr(,"assign") [1] 0 1 > F2 <- Formula(y1 + y2 ~ x3) > length(F2) [1] 1 1 > mf2 <- model.frame(F2, data = dat) > mf2 y1 y2 x3 2 0.70 a b 3 0.65 b a > model.response(mf2) NULL > model.part(F2, data = mf2, lhs = 1) y1 y2 2 0.70 a 3 0.65 b > model.part(F1, data = mf1, lhs = 1, drop = TRUE) 1 2 3 -0.1984509 -0.3566749 -0.4307829 > F3 <- Formula(y1 + y2 | log(y3) ~ x1 + I(x2^2) | 0 + + log(x1) | x3/x4) > F3 y1 + y2 | log(y3) ~ x1 + I(x2^2) | 0 + log(x1) | x3/x4 > length(F3) [1] 2 3 > attr(F3, "lhs") [[1]] y1 + y2 [[2]] log(y3) > formula(F3) y1 + y2 | log(y3) ~ x1 + I(x2^2) | 0 + log(x1) | x3/x4 > formula(F3, lhs = 2, rhs = -2) log(y3) ~ x1 + I(x2^2) | x3/x4 > formula(F3, lhs = c(TRUE, FALSE), rhs = 0) y1 + y2 ~ 0 > terms(F3) ~y1 + y2 + log(y3) + (x1 + I(x2^2)) + (0 + log(x1)) + x3/x4 attr(,"variables") list(y1, y2, log(y3), x1, I(x2^2), log(x1), x3, x4) attr(,"factors") y1 y2 log(y3) x1 I(x2^2) log(x1) x3 x3:x4 y1 1 0 0 0 0 0 0 0 y2 0 1 0 0 0 0 0 0 log(y3) 0 0 1 0 0 0 0 0 x1 0 0 0 1 0 0 0 0 I(x2^2) 0 0 0 0 1 0 0 0 log(x1) 0 0 0 0 0 1 0 0 x3 0 0 0 0 0 0 1 2 x4 0 0 0 0 0 0 0 1 attr(,"term.labels") [1] "y1" "y2" "log(y3)" "x1" "I(x2^2)" "log(x1)" [7] "x3" "x3:x4" attr(,"order") [1] 1 1 1 1 1 1 1 2 attr(,"intercept") [1] 0 attr(,"response") [1] 0 attr(,".Environment") <environment: R_GlobalEnv> > formula(terms(F3)) ~y1 + y2 + log(y3) + (x1 + I(x2^2)) + (0 + log(x1)) + x3/x4 > formula(terms(F3, lhs = 2, rhs = -2)) log(y3) ~ x1 + I(x2^2) + x3/x4 > formula(terms(F3, lhs = c(TRUE, FALSE), rhs = 0)) ~y1 + y2 > mf3 <- model.frame(F3, data = dat, subset = y1 < 0.75, + weights = x1) > mf3 y1 y2 log(y3) x1 I(x2^2) log(x1) x3 x4 (weights) 2 0.70 a -1.771957 0.26 0.2116 -1.347074 b b 0.26 3 0.65 b -1.272966 0.03 0.1369 -3.506558 a a 0.03 > model.matrix(F3, data = mf3, rhs = 2) log(x1) 2 -1.347074 3 -3.506558 attr(,"assign") [1] 1 > model.part(F3, data = mf3, lhs = 1) y1 y2 2 0.70 a 3 0.65 b > model.part(F3, data = mf3, lhs = 2) log(y3) 2 -1.771957 3 -1.272966 > model.weights(mf3) [1] 0.26 0.03 > update(F1, . ~ . - x1 | . + x1) log(y1) ~ x2 | I(x1^2) + x1 > update(F1, . + y2 | y3 ~ .) log(y1) + y2 | y3 ~ x1 + x2 | I(x1^2) > as.Formula(y1 ~ x1, y2 ~ x2, ~x3) y1 | y2 ~ x1 | x2 | x3 > ivcoef <- function(formula, data, subset, na.action, + ...) { + mf <- match.call(expand.dots = FALSE) + m <- match(c("formula", "data", .... [TRUNCATED] > ivcoef(log(y1) ~ x1 | x2, data = dat) (Intercept) x1 -0.169027 -1.260073 *** Run successfully completed *** > proc.time() user system elapsed 0.32 0.15 0.42 ... incomplete output. Crash? 'Formula.Rnw'... failed to complete the test Flavor: r-devel-windows-x86_64