colmses: any metrics for a continuous response variable

In Rfast2: A Collection of Efficient and Extremely Fast R Functions II

any metrics for a continuous response variable

Description

any metrics for a continuous response variable.

Usage

colmses(y, yhat, parallel = FALSE)
colmaes(y, yhat, parallel = FALSE)
colpkl(y, yhat, parallel = FALSE)
colukl(y, yhat, parallel = FALSE)

Arguments

y	A numerical vector.
yhat	A numerical matrix with with the predictions.
parallel	If you want parallel computations set this equal to TRUE.

Details

The mean squared errors, mean absolute errors, and Kullback-Leibler divergence for percentages (colpkl) and non-negative values or discrete values (colukl) are computed.

Value

A vector with length equal to the number of columns of the "yhat" argument containing the relevant values computed for each column.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

See Also

colaccs, bigknn.cv, mmpc, pc.sel

Examples

## 20 variables, hence 20 MSEs will be calculated
y <- rnorm(100, 1, 0.6)
yhat <- matrix( rnorm(100 * 20), ncol = 20 )
a <- colmses(y, yhat)

Rfast2 documentation built on May 29, 2024, 8:45 a.m.