Define M1 specifications
Usage
build_M1(
M1_model = 0,
M1_re = 0,
updateM1 = FALSE,
M1_use_prior = FALSE,
M2_use_prior = FALSE,
M_prior = 0.4,
M_prior_sd = 0.35,
M1_indices = NA,
linkages = NULL
)Arguments
- M1_model
Vector or scalar specifying the M1 structural fixed- effects model. Either an integer code or the equivalent string alias (both forms are accepted; the integer code is canonical):
0/"fixed"– use the inputM1_base(no estimation).1/"sex_age_invariant"– estimate oneM1_{spp}.2/"sex_specific"– estimateM1_{spp, sex}.3/"sex_age_specific"– estimateM1_{spp, sex, age}.4,5– soft-deprecated env-driven codes; use thelinkagesargument instead. Seevignette("environmental-linkages").
- M1_re
Vector or scalar specifying the M1 random-effects model. Either an integer code or the equivalent string alias:
0/"none",1/"iid_age",2/"iid_year",3/"iid_age_year",4/"ar1_age",5/"ar1_year",6/"ar1_age_year".- updateM1
If using initial parameters, use M1 fixed effects from data (
M1_base) instead. DefaultFALSE.- M1_use_prior
Vector or scalar; if
TRUE, apply the lognormalM_prior/M_prior_sdtolog_M1directly.- M2_use_prior
Vector or scalar; if
TRUE, apply the lognormal prior toM1 + M2in multi-species models.- M_prior
Mean (natural-scale) of the lognormal prior on M.
- M_prior_sd
SD (log-scale) of the lognormal prior on M.
- M1_indices
Soft-deprecated. Vector of column indices into
env_data(excludingYear) for environmentally linked M1 whenM1_model %in% c(4, 5). Use thelinkagesargument instead; seevignette("environmental-linkages").- linkages
Optional named list of
linkage_spec()objects keyed by M parameter name (currently the only valid key is"log_M1"). Each spec describes howlog_M1depends on environmental covariates and on stratifying factors (species, sex, age). The offset enters additively (on the log scale) inside theM1_at_agecompute. A row'sage_bin == NAbroadcasts the offset across ages; specific values pin it to that age slice.
Examples
if (FALSE) { # \dontrun{
# Sex/age-invariant M with a temperature linkage on log_M1
build_M1(
M1_model = "sex_age_invariant",
linkages = list(
log_M1 = linkage_spec(
formula = ~ temp,
by = ~ species,
priors = list(temp = normal(0, 0.5))
)
)
)
} # }