mkTMBStruc: Extract info from formulas, reTrms, etc., format for TMB

In glmmTMB: Generalized Linear Mixed Models using Template Model Builder

Extract info from formulas, reTrms, etc., format for TMB

Description

Extract info from formulas, reTrms, etc., format for TMB

Usage

mkTMBStruc(
  formula,
  ziformula,
  dispformula,
  combForm,
  mf,
  fr,
  yobs,
  respCol,
  weights = NULL,
  contrasts,
  family,
  se = NULL,
  call = NULL,
  verbose = NULL,
  ziPredictCode = "corrected",
  doPredict = 0,
  whichPredict = integer(0),
  REML = FALSE,
  start = NULL,
  map = NULL,
  sparseX = NULL,
  control = glmmTMBControl(),
  old_smooths = NULL,
  priors = NULL
)

Arguments

formula	combined fixed and random effects formula, following lme4 syntax.
ziformula	a one-sided (i.e., no response variable) formula for zero-inflation combining fixed and random effects: the default ~0 specifies no zero-inflation. Specifying ~. sets the zero-inflation formula identical to the right-hand side of formula (i.e., the conditional effects formula); terms can also be added or subtracted. When using ~. as the zero-inflation formula in models where the conditional effects formula contains an offset term, the offset term will automatically be dropped. The zero-inflation model uses a logit link.
dispformula	a one-sided formula for dispersion combining fixed and random effects: the default ~1 specifies the standard dispersion given any family. The argument is ignored for families that do not have a dispersion parameter. For an explanation of the dispersion parameter for each family, see sigma. The dispersion model uses a log link. In Gaussian mixed models, dispformula=~0 fixes the residual variance to be 0 (actually a small non-zero value), forcing variance into the random effects. The precise value can be controlled via control=glmmTMBControl(zero_dispval=...); the default value is sqrt(.Machine$double.eps).
combForm	combined formula
mf	call to model frame
fr	model frame
yobs	observed y
respCol	response column
weights	model weights (for binomial-type models, used as size/number of trials)
contrasts	an optional list, e.g., list(fac1="contr.sum"). See the contrasts.arg of model.matrix.default.
family	family object
se	(logical) compute standard error?
call	original glmmTMB call
verbose	whether progress indication should be printed to the console.
ziPredictCode	zero-inflation code
doPredict	flag to enable sds of predictions
whichPredict	which observations in model frame represent predictions
REML	whether to use REML estimation rather than maximum likelihood.
start	starting values, expressed as a list with possible components beta, betazi, betadisp (fixed-effect parameters for conditional, zero-inflation, dispersion models); b, bzi, bdisp (conditional modes for conditional, zero-inflation, and dispersion models); theta, thetazi, thetadisp (random-effect parameters, on the standard deviation/Cholesky scale, for conditional, z-i, and disp models); psi (extra family parameters, e.g., shape for Tweedie models).
map	a list specifying which parameter values should be fixed to a constant value rather than estimated. map should be a named list containing factors corresponding to a subset of the internal parameter names (see start parameter). Distinct factor values are fitted as separate parameter values, NA values are held fixed: e.g., map=list(beta=factor(c(1,2,3,NA))) would fit the first three fixed-effect parameters of the conditional model and fix the fourth parameter to its starting value. In general, users will probably want to use start to specify non-default starting values for fixed parameters. See MakeADFun for more details.
sparseX	see glmmTMB
control	control parameters, see glmmTMBControl.
old_smooths	(optional) smooth components from a previous fit: used when constructing a new model structure for prediction from an existing model. A list of smooths for each model component; each smooth has sm and re elements
priors	see priors

glmmTMB documentation built on Sept. 30, 2024, 9:34 a.m.