Extract the model matrix (X) from a fitted model object.
# S3 method for ssn_lm
model.matrix(object, ...)
# S3 method for ssn_glm
model.matrix(object, ...)The model matrix (of the fixed effects), whose rows represent observations and whose columns represent explanatory variables corresponding to each fixed effect.
# 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"
)
model.matrix(ssn_mod)
#> (Intercept) ELEV_DEM
#> 1 1 1947
#> 2 1 1952
#> 3 1 1958
#> 4 1 1923
#> 5 1 1932
#> 6 1 1940
#> 7 1 1940
#> 8 1 1945
#> 9 1 1948
#> 10 1 1950
#> 11 1 1949
#> 12 1 1950
#> 13 1 1951
#> 14 1 1977
#> 15 1 1984
#> 16 1 1993
#> 17 1 2007
#> 18 1 2009
#> 19 1 2012
#> 20 1 2023
#> 21 1 2023
#> 22 1 2026
#> 23 1 1988
#> 24 1 2013
#> 25 1 2015
#> 26 1 2015
#> 27 1 2038
#> 28 1 2052
#> 29 1 2066
#> 30 1 2085
#> 31 1 1975
#> 32 1 1982
#> 33 1 1999
#> 34 1 2002
#> 35 1 1997
#> 36 1 2006
#> 37 1 2026
#> 38 1 2036
#> 39 1 2046
#> 40 1 2050
#> 41 1 2071
#> 42 1 2077
#> 43 1 2016
#> 44 1 2034
#> 45 1 2042
#> attr(,"assign")
#> [1] 0 1