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

Description Usage Arguments

View source: R/glmmTMB.R

Description

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

Usage

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

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 containing only fixed 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

weights, as in glm. Not automatically scaled to have sum 1.

contrasts

an optional list, e.g., list(fac1="contr.sum"). See the contrasts.arg of model.matrix.default.

size

number of trials in binomial and betabinomial families

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, betad (fixed-effect parameters for conditional, zero-inflation, dispersion models); b, bzi (conditional modes for conditional and zero-inflation models); theta, thetazi (random-effect parameters, on the standard deviation/Cholesky scale, for conditional and z-i models); thetaf (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.

zioffset

offset for zero-inflated model

doffset

offset for dispersion model


glmmTMB documentation built on July 20, 2021, 9:06 a.m.