RsquareAdj {vegan} | R Documentation |
Adjusted R-square
Description
The functions finds the adjusted R-square.
Usage
## Default S3 method:
RsquareAdj(x, n, m, ...)
## S3 method for class 'rda'
RsquareAdj(x, ...)
## S3 method for class 'cca'
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 |
... |
Other arguments (ignored) except in the case of cca in
which these arguments are passed to |
Details
The default method finds the adjusted R^2
from the unadjusted R^2
, 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^2
may not be available in some cases, and then the
functions will return NA
. There is no adjusted
R^2
in partial ordination, and R^2
values are available only for gaussian
models in
glm
.
The adjusted, R^2
of cca
is computed using a
permutation approach developed by Peres-Neto et al. (2006). By
default 1000 permutations are used.
Value
The functions return a list of items r.squared
and
adj.r.squared
.
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)