coef extracts fitted model coefficients from fitted model objects.
coefficients is an alias for it.
Usage
# S3 method for ssn_lm
coef(object, type = "fixed", ...)
# S3 method for ssn_lm
coefficients(object, type = "fixed", ...)
# S3 method for ssn_glm
coef(object, type = "fixed", ...)
# S3 method for ssn_glm
coefficients(object, type = "fixed", ...)Arguments
- object
- type
"fixed"for fixed effect coefficients,"tailup"for tailup covariance parameter coefficients,"taildown"for taildown covariance parameter coefficients,"euclid"for Euclidean covariance parameter coefficients,"nugget"for nugget covariance parameter coefficients,"dispersion"for the dispersion parameter coefficient (ssn_glm()objects),"randcov"for random effect variance coefficients, or"ssn"for all of the tailup, taildown, Euclidean, nugget, and dispersion (ssn_glm()objects) parameter coefficients. Defaults to"fixed".- ...
Other arguments. Not used (needed for generic consistency).
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"
)
coef(ssn_mod)
#> (Intercept) ELEV_DEM
#> 71.32316197 -0.02882225
coef(ssn_mod, type = "tailup")
#> de range
#> 4.415469e+00 1.174539e+06
#> attr(,"class")
#> [1] "tailup_exponential"
coefficients(ssn_mod)
#> (Intercept) ELEV_DEM
#> 71.32316197 -0.02882225