tests/andersondarling_behaviour.r

In matrixTests: Fast Statistical Hypothesis Tests on Rows and Columns of Matrices

library(matrixTests)

#--- special argument cases ----------------------------------------------------

# x can be a vector
x <- rnorm(9)
X <- matrix(x, nrow=1)
stopifnot(all.equal(row_andersondarling(x), row_andersondarling(X)))

# x can be numeric data.frame
x <- cbind(iris[,1:4], iris[,1:4])
X <- as.matrix(x)
stopifnot(all.equal(row_andersondarling(x), row_andersondarling(X)))

# x can have 0 rows
x <- matrix(0, nrow=0, ncol=4)
stopifnot(all.equal(nrow(row_andersondarling(x)), 0))

# x can have 0 rows and 0 columns
x <- matrix(0, nrow=0, ncol=0)
stopifnot(all.equal(nrow(row_andersondarling(x)), 0))


#--- missing values ------------------------------------------------------------

# missing values in x are removed
x <- c(NA,NA,rnorm(8),NA)
res1 <- row_andersondarling(x)
res2 <- row_andersondarling(x[!is.na(x)])
stopifnot(all.equal(res1, res2))

# no difference between NA and NaN in x
x1 <- c(NA,NA,1:8,NA)
x2 <- c(NaN,NaN,1:8,NaN)
res1 <- row_andersondarling(x1)
res2 <- row_andersondarling(x2)
stopifnot(all.equal(res1, res2))

# everything can be NA
x <- rep(NA_integer_, 8)
res <- suppressWarnings(row_andersondarling(x))
stopifnot(all.equal(res$obs, 0))


#--- rownames ------------------------------------------------------------------

# when not provided - numbers are used instead.
x <- matrix(rnorm(20), nrow=2)
res <- row_andersondarling(x)
stopifnot(all.equal(rownames(res), c("1", "2")))

# when provided - preserved (matrix)
x <- matrix(rnorm(20), nrow=2, dimnames=list(c("A", "B")))
res <- row_andersondarling(x)
stopifnot(all.equal(rownames(res), rownames(x)))

# when provided - preserved (data.frame)
x <- data.frame(matrix(rnorm(20), nrow=2, dimnames=list(c("A", "B"))))
res <- row_andersondarling(x)
stopifnot(all.equal(rownames(res), rownames(x)))

# when duplicated - made unique
x <- matrix(rnorm(40), nrow=4, dimnames=list(c("A", "A", "B", "B")))
res <- row_andersondarling(x)
stopifnot(all.equal(rownames(res), make.unique(rownames(x))))