# exVar: calculate variance of a distribution stemming from prediction... In Morpho: Calculations and Visualisations Related to Geometric Morphometrics

 exVar R Documentation

## calculate variance of a distribution stemming from prediction models

### Description

calculates a quotient of the overall varriance within a predicted distribution to that from the original one. This function calculates a naive extension of the univariate R^2-value by dividing the variance in the predicted dat by the variance of the original data. No additional adjustments are made!!

### Usage

``````exVar(model, ...)

## S3 method for class 'lm'
exVar(model, ...)

## S3 method for class 'mvr'
exVar(model, ncomp, val = FALSE, ...)
``````

### Arguments

 `model` a model of classes "lm" or "mvr" (from the package "pls") `...` currently unused additional arguments. `ncomp` How many latent variables to use (only for mvr models) `val` use cross-vaildated predictions (only for mvr models)

### Value

returns the quotient.

### Note

The result is only!! a rough estimate of the variance explained by a multivariate model. And the result can be misleading - especially when there are many predictor variables involved. If one is interested in the value each factor/covariate explains, we recommend a 50-50 MANOVA perfomed by the R-package "ffmanova", which reports this value factor-wise.

Stefan Schlager

### References

Langsrud O, Juergensen K, Ofstad R, Naes T. 2007. Analyzing Designed Experiments with Multiple Responses Journal of Applied Statistics 34:1275-1296.

### Examples

``````
lm1 <- lm(as.matrix(iris[,1:4]) ~ iris[,5])
exVar(lm1)
``````

Morpho documentation built on June 22, 2024, 7:19 p.m.