By default returns a named list of all four design matrices the TMB
template consumed: X_q0, X_alpha, Z_q0, Z_alpha. Use what
to select a single matrix. X_q0 and X_alpha are zero-copy
references to fit$formula_details; Z_q0 and Z_alpha are
recomputed via the internal builder.
Usage
# S3 method for class 'beezdemand_tmb'
model.matrix(object, what = NULL, ...)Value
Named list of numeric matrices, or a single numeric matrix when
what is set. NULL (with a message) when a degenerate Z is requested.
Details
Returning a named list (vs the single matrix lm/lme4 return) is
intentional: the TMB tier has two fixed-effect linear predictors
(one per nonlinear parameter), not one.
Examples
# \donttest{
data(apt)
fit <- fit_demand_tmb(apt, equation = "exponential", verbose = 0)
#> equation='exponential': Dropped 14 zero-consumption observations (146 remaining).
str(model.matrix(fit))
#> List of 4
#> $ X_q0 : num [1:146, 1] 1 1 1 1 1 1 1 1 1 1 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : chr [1:146] "1" "2" "3" "4" ...
#> .. ..$ : chr "(Intercept)"
#> ..- attr(*, "assign")= int 0
#> $ X_alpha: num [1:146, 1] 1 1 1 1 1 1 1 1 1 1 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : chr [1:146] "1" "2" "3" "4" ...
#> .. ..$ : chr "(Intercept)"
#> ..- attr(*, "assign")= int 0
#> $ Z_q0 : num [1:146, 1] 1 1 1 1 1 1 1 1 1 1 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : chr [1:146] "1" "2" "3" "4" ...
#> .. ..$ : chr "(Intercept)"
#> $ Z_alpha: num [1:146, 1] 1 1 1 1 1 1 1 1 1 1 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : chr [1:146] "1" "2" "3" "4" ...
#> .. ..$ : chr "(Intercept)"
head(model.matrix(fit, what = "X_q0"))
#> (Intercept)
#> 1 1
#> 2 1
#> 3 1
#> 4 1
#> 5 1
#> 6 1
# }