Fast binning of numeric vector into equidistant bins

Missing values (NA, Inf, NaN) are added at the end of the vector as the last bin returned if missinglast is set to TRUE

Usage

NNS_bin(x, width, origin = 0, missinglast = FALSE)

Arguments

x: A matrix of regressor variables. Must have the same number of rows as the length of y.
width: The width of the bins
origin: The starting point for the bins. Any number smaller than origin will be disregarded
missinglast: Boolean. Should the missing observations be added as a separate element at the end of the returned count vector.

Value

An list with elements counts (the frequencies), origin (the origin), width (the width), missing (the number of missings), and last_bin_is_missing (boolean) telling whether the missinglast is true or not.

Examples

if (FALSE) { # \dontrun{
set.seed(1)
x <- sample(10, 20, replace = TRUE)
NNS_bin(x, 15)
} # }