pglmm_matrix_structure | R Documentation |
pglmm_matrix_structure
produces the entire
covariance matrix structure (V) when you specify random effects.pglmm_matrix_structure
produces the entire
covariance matrix structure (V) when you specify random effects.
pglmm_matrix_structure(
formula,
data = list(),
family = "binomial",
cov_ranef,
repulsion = FALSE,
ss = 1,
cpp = TRUE
)
communityPGLMM.matrix.structure(
formula,
data = list(),
family = "binomial",
cov_ranef,
repulsion = FALSE,
ss = 1,
cpp = TRUE
)
formula |
A two-sided linear formula object describing the mixed effects of the model. To specify that a random term should have phylogenetic covariance matrix along
with non-phylogenetic one, add Note that correlated random terms are not allowed. For example,
|
data |
A |
family |
Either "gaussian" for a Linear Mixed Model, or
"binomial" or "poisson" for Generalized Linear Mixed Models.
"family" should be specified as a character string (i.e., quoted). For binomial and
Poisson data, we use the canonical logit and log link functions, respectively.
Binomial data can be either presence/absence, or a two-column array of 'successes' and 'failures'.
For both binomial and Poisson data, we add an observation-level
random term by default via |
cov_ranef |
A named list of covariance matrices of random terms. The names should be the
group variables that are used as random terms with specified covariance matrices
(without the two underscores, e.g. |
repulsion |
When there are nested random terms specified, |
ss |
Which of the |
cpp |
Whether to use C++ function for optim. Default is TRUE. Ignored if |
A design matrix.
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