RsquareAdj.Rd
The functions finds the adjusted R-square.
# S3 method for default RsquareAdj(x, n, m, ...) # S3 method for rda RsquareAdj(x, ...) # S3 method for cca RsquareAdj(x, permutations = 1000, ...)
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 |
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.
The functions return a list of items r.squared
and
adj.r.squared
.
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.
varpart
uses RsquareAdj
.
#> $r.squared #> [1] 0.5265047 #> #> $adj.r.squared #> [1] 0.4367038 #>#> $r.squared #> [1] 0.4471676 #> #> $adj.r.squared #> [1] 0.3429184 #>## default method RsquareAdj(0.8, 20, 5)#> [1] 0.7285714