View source: R/find_parameters_bayesian.R
find_parameters.BGGM | R Documentation |
Returns the names of model parameters, like they typically
appear in the summary()
output. For Bayesian models, the parameter
names equal the column names of the posterior samples after coercion
from as.data.frame()
.
## S3 method for class 'BGGM'
find_parameters(x, component = "correlation", flatten = FALSE, ...)
## S3 method for class 'brmsfit'
find_parameters(
x,
effects = "all",
component = "all",
flatten = FALSE,
parameters = NULL,
...
)
x |
A fitted model. |
component |
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):
|
flatten |
Logical, if |
... |
Currently not used. |
effects |
Should variables for fixed effects ( |
parameters |
Regular expression pattern that describes the parameters that should be returned. |
A list of parameter names. For simple models, only one list-element,
conditional
, is returned. For more complex models, the returned list may
have following elements:
conditional
, the "fixed effects" part from the model
random
, the "random effects" part from the model
zero_inflated
, the "fixed effects" part from the zero-inflation component
of the model
zero_inflated_random
, the "random effects" part from the zero-inflation
component of the model
smooth_terms
, the smooth parameters
Furthermore, some models, especially from brms, can also return auxiliary parameters. These may be one of the following:
sigma
, the residual standard deviation (auxiliary parameter)
dispersion
, the dispersion parameters (auxiliary parameter)
beta
, the beta parameter (auxiliary parameter)
simplex
, simplex parameters of monotonic effects (brms only)
mix
, mixture parameters (brms only)
shiftprop
, shifted proportion parameters (brms only)
Models of class BGGM additionally can return the elements correlation
and intercept
.
Models of class BFBayesFactor additionally can return the element
extra
.
data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
find_parameters(m)
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