Compute a pseudo r-squared

Compute a pseudo r-squared for a fitted model object.

# S3 method for ssn_lm
pseudoR2(object, adjust = FALSE, ...)

# S3 method for ssn_glm
pseudoR2(object, adjust = FALSE, ...)

Arguments

object

A fitted model object from ssn_lm() or ssn_glm().

adjust

A logical indicating whether the pseudo r-squared should be adjusted to account for the number of explanatory variables. The default is FALSE.

...

Other arguments. Not used (needed for generic consistency).

Value

The pseudo r-squared as a numeric vector.

Details

Several pseudo r-squared statistics exist for in the literature. We define this pseudo r-squared as one minus the ratio of the deviance of a full model relative to the deviance of a null (intercept only) model. This pseudo r-squared can be viewed as a generalization of the classical r-squared definition seen as one minus the ratio of error sums of squares from the full model relative to the error sums of squares from the null model. If adjusted, the adjustment is analogous to the the classical r-squared adjustment.

Examples

# Copy the mf04p .ssn data to a local directory and read it into R
# When modeling with your .ssn object, you will load it using the relevant
# path to the .ssn data on your machine
copy_lsn_to_temp()
temp_path <- paste0(tempdir(), "/MiddleFork04.ssn")
mf04p <- ssn_import(temp_path, overwrite = TRUE)

ssn_mod <- ssn_lm(
  formula = Summer_mn ~ ELEV_DEM,
  ssn.object = mf04p,
  tailup_type = "exponential",
  additive = "afvArea"
)
pseudoR2(ssn_mod)
#> [1] 0.5854895