sirt (version 4.1-15)

monoreg.rowwise: Monotone Regression for Rows or Columns in a Matrix

Description

Monotone (isotone) regression for rows (monoreg.rowwise) or columns (monoreg.colwise) in a matrix.

Usage

monoreg.rowwise(yM, wM)

monoreg.colwise(yM, wM)

Value

Matrix with fitted values

Arguments

yM

Matrix with dependent variable for the regression. Values are assumed to be sorted.

wM

Matrix with weights for every entry in the yM matrix.

Author

Alexander Robitzsch

The monoreg function from the fdrtool package is simply extended to handle matrix input.

See Also

See also the monoreg function from the fdrtool package.

Examples

Run this code
y <- c(22.5, 23.33, 20.83, 24.25 )
w <- c( 3,3,3,2)
# define matrix input
yM <- matrix( 0, nrow=2, ncol=4 )
wM <- yM
yM[1,] <- yM[2,] <- y
wM[1,] <- w
wM[2,] <- c(1,3,4, 3 )

# fit rowwise monotone regression
monoreg.rowwise( yM, wM )
# compare results with monoreg function from fdrtool package
if (FALSE) {
miceadds::library_install("fdrtool")
fdrtool::monoreg(x=yM[1,], w=wM[1,])$yf
fdrtool::monoreg(x=yM[2,], w=wM[2,])$yf
}

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