postResampleSpectro: Calculates performance indictors across resamples

In spectacles: Storing, Manipulating and Analysis Spectroscopy and Associated Data

Calculates performance indictors across resamples

Description

Given two numeric vectors of data, the root mean squared error, the R-squared, the bias, the RPD, the RPIQ, the CCC and the standard error are calculated. For two factors, the overall agreement rate and Kappa are determined.

Usage

postResampleSpectro(pred, obs)
spectroSummary(data, lev = NULL, model = NULL)

Arguments

data	a data frame or matrix with columns obs and pred for the observed and predicted outcomes
lev	a character vector of factors levels for the response. In regression cases, this would be NULL.
model	a character string for the model name
pred	A vector of numeric data
obs	A vector of numeric data

Details

This function extends postResample in the caret package.

Author(s)

Pierre Roudier, adapted from code from Max Kuhn

Examples

predicted <-  matrix(rnorm(50), ncol = 5)
observed <- rnorm(10)
apply(predicted, 2, postResampleSpectro, obs = observed)

spectacles documentation built on July 10, 2023, 1:59 a.m.