Change starting parameters, either by residual method or by user input (start)
startParams(
parameters,
formula,
ziformula,
dispformula,
fr,
yobs,
weights,
size = NULL,
Xd = NULL,
XdS = NULL,
family,
condReStruc,
start = NULL,
sparseX = NULL,
start_method = list(method = NULL, jitter.sd = 0)
)current formula, containing both fixed & random effects
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.
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).
model frame
observed y
weights, as in glm. Not automatically scaled to have sum 1.
number of trials in binomial and betabinomial families
family object
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).
see glmmTMB
Options to initialise the starting values for rr parameters; jitter.sd adds variation to the starting values of latent variables when start = "res".