Returns the coefficients from a model.
# S3 method for zeroinfl
get_parameters(x, component = "all", ...)
For models with smooth terms or zero-inflation component, a data frame with three columns: the parameter names, the related point estimates and the component.
A fitted model.
Which type of parameters to return, such as parameters for the conditional model, the zero-inflated part of the model, the dispersion term, the instrumental variables or marginal effects be returned? Applies to models with zero-inflated and/or dispersion formula, or to models with instrumental variables (so called fixed-effects regressions), or models with marginal effects (from mfx). See details in section Model Components .May be abbreviated. Note that the conditional component also refers to the count or mean component - names may differ, depending on the modeling package. There are three convenient shortcuts (not applicable to all model classes):
component = "all"
returns all possible parameters.
If component = "location"
, location parameters such as conditional
,
zero_inflated
, smooth_terms
, or instruments
are returned (everything
that are fixed or random effects - depending on the effects
argument -
but no auxiliary parameters).
For component = "distributional"
(or "auxiliary"
), components like
sigma
, dispersion
, beta
or precision
(and other auxiliary
parameters) are returned.
Currently not used.
Possible values for the component
argument depend on the model class.
Following are valid options:
"all"
: returns all model components, applies to all models, but will only
have an effect for models with more than just the conditional model component.
"conditional"
: only returns the conditional component, i.e. "fixed effects"
terms from the model. Will only have an effect for models with more than
just the conditional model component.
"smooth_terms"
: returns smooth terms, only applies to GAMs (or similar
models that may contain smooth terms).
"zero_inflated"
(or "zi"
): returns the zero-inflation component.
"dispersion"
: returns the dispersion model component. This is common
for models with zero-inflation or that can model the dispersion parameter.
"instruments"
: for instrumental-variable or some fixed effects regression,
returns the instruments.
"nonlinear"
: for non-linear models (like models of class nlmerMod
or
nls
), returns staring estimates for the nonlinear parameters.
"correlation"
: for models with correlation-component, like gls
, the
variables used to describe the correlation structure are returned.
"location"
: returns location parameters such as conditional
,
zero_inflated
, smooth_terms
, or instruments
(everything that are
fixed or random effects - depending on the effects
argument - but no
auxiliary parameters).
"distributional"
(or "auxiliary"
): components like sigma
, dispersion
,
beta
or precision
(and other auxiliary parameters) are returned.
Special models
Some model classes also allow rather uncommon options. These are:
mhurdle: "infrequent_purchase"
, "ip"
, and "auxiliary"
BGGM: "correlation"
and "intercept"
BFBayesFactor, glmx: "extra"
averaging:"conditional"
and "full"
mjoint: "survival"
mfx: "precision"
, "marginal"
betareg, DirichletRegModel: "precision"
mvord: "thresholds"
and "correlation"
clm2: "scale"
selection: "selection"
, "outcome"
, and "auxiliary"
For models of class brmsfit
(package brms), even more options are
possible for the component
argument, which are not all documented in detail
here.
data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
get_parameters(m)
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