vegan (version 2.4-0)

RsquareAdj: Adjusted R-square

Description

The functions finds the adjusted R-square.

Usage

"RsquareAdj"(x, n, m, ...)
"RsquareAdj"(x, ...)
"RsquareAdj"(x, permutations = 1000, ...)

Arguments

x

Unadjusted R-squared or an object from which the terms for evaluation or adjusted R-squared can be found.

n, m

Number of observations and number of degrees of freedom in the fitted model.

permutations

Number of permutations to use when computing the adjusted R-squared for a cca. The permutations can be calculated in parallel by specifying the number of cores which is passed to permutest

...

Other arguments (ignored) except in the case of cca in which these arguments are passed to permutest.

Value

r.squared and adj.r.squared.

Details

The default method finds the adjusted R-squared from the unadjusted R-squared, number of observations, and number of degrees of freedom in the fitted model. The specific methods find this information from the fitted result object. There are specific methods for rda, cca, lm and glm. Adjusted, or even unadjusted, R-squared may not be available in some cases, and then the functions will return NA. There is no adjusted in partial rda, and R-squared values are available only for gaussian models in glm.

The adjusted, $R-squared$ of cca is computed using a permutation approach developed by Peres-Neto et al. (2006). By default 1000 permutations are used. The raw $R-squared$ of partial rda gives the proportion explained after removing the variation due to conditioning (partial) terms; Legendre et al. (2011) call this semi-partial $R-squared$. The adjusted $R-squared$ is found as the difference of adjusted $R-squared$ values of joint effect of partial and constraining terms and partial term alone, and it is the same as the adjusted $R-squared$ of component [a] = X1|X2 in two-component variation partition in varpart.

References

Legendre, P., Oksanen, J. and ter Braak, C.J.F. (2011). Testing the significance of canonical axes in redundancy analysis. Methods in Ecology and Evolution 2, 269--277. Peres-Neto, P., P. Legendre, S. Dray and D. Borcard. 2006. Variation partitioning of species data matrices: estimation and comparison of fractions. Ecology 87, 2614--2625.

See Also

varpart uses RsquareAdj.

Examples

data(mite)
data(mite.env)
## rda
m <- rda(decostand(mite, "hell") ~  ., mite.env)
RsquareAdj(m)
## cca
m <- cca(decostand(mite, "hell") ~  ., mite.env)
RsquareAdj(m)
## default method
RsquareAdj(0.8, 20, 5)