sigma() returns the fitted scale-like parameter from a drmTMB model. For
univariate Gaussian location-scale models this is the fitted residual
sigma_i vector on the response scale. For Student-t models this is the
Student-t scale parameter; when nu > 2, the residual standard deviation is
sigma * sqrt(nu / (nu - 2)). For lognormal models this is the fitted
standard deviation of log(y). For Gamma models this is the fitted
coefficient of variation. For beta and beta-binomial models this is the
public scale parameter where internal precision is phi = 1 / sigma^2.
Cumulative-logit ordinal, Poisson, and zero-inflated Poisson models have no
fitted residual scale parameter and return a fixed unit dispersion vector
for consistency with base-R sigma() conventions. For
negative-binomial 2, zero-truncated negative-binomial 2, hurdle
negative-binomial 2, and zero-inflated negative-binomial 2 models this is
the fitted overdispersion scale in the untruncated NB2 component
Var(y | component) = mu + sigma^2 * mu^2. For bivariate Gaussian models
it returns a list with fitted sigma1 and
sigma2 vectors.
Usage
# S3 method for class 'drmTMB'
sigma(object, ...)Value
A numeric vector for univariate models, or a named list of numeric vectors for bivariate Gaussian models.