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dynamite
Output to draws_df
FormatConverts the output from a dynamite()
call to a
draws_df
format of the posterior package, enabling the use
of diagnostics and plotting methods of posterior and bayesplot
packages. Note that this function returns variables in a wide format,
whereas as.data.frame.dynamitefit()
uses the long format.
# S3 method for dynamitefit
as_draws_df(
x,
parameters = NULL,
responses = NULL,
types = NULL,
times = NULL,
groups = NULL,
...
)# S3 method for dynamitefit
as_draws(x, parameters = NULL, responses = NULL, types = NULL, ...)
A draws_df
object.
A draws_df
object.
[dynamitefit
]
The model fit object.
[character()
]
Parameter(s) for which the samples
should be extracted. Possible options can be found with function
get_parameter_names()
. Default is all parameters of specific type for
all responses. This argument is mutually exclusive with types
.
[character()
]
Response(s) for which the samples
should be extracted. Possible options are elements of
unique(x$priors$response)
, and the default is this entire vector.
Ignored if the argument parameters
is supplied.
omega_alpha
, and omega_psi
. See also get_parameter_types()
.
[character()
]
Type(s) of the parameters for which the
samples should be extracted. See details of possible values. Default is
all values listed in details except spline coefficients omega
.
This argument is mutually exclusive with parameters
.
[double()
]
Time point(s) to keep. If NULL
(the default), all time points are kept.
[character()
]
Group name(s) to keep. If NULL
(the default), all groups are kept.
Ignored.
You can use the arguments parameters
, responses
and types
to extract
only a subset of the model parameters (i.e., only certain types of
parameters related to a certain response variable).
See potential values for the types argument in as.data.frame.dynamitefit()
and get_parameter_names()
for potential values for parameters
argument.
Model outputs
as.data.frame.dynamitefit()
,
as.data.table.dynamitefit()
,
coef.dynamitefit()
,
confint.dynamitefit()
,
dynamite()
,
get_code()
,
get_data()
,
get_parameter_dims()
,
get_parameter_names()
,
get_parameter_types()
,
ndraws.dynamitefit()
,
nobs.dynamitefit()
data.table::setDTthreads(1) # For CRAN
as_draws(gaussian_example_fit, types = c("sigma", "beta"))
# Compute MCMC diagnostics using the posterior package
posterior::summarise_draws(as_draws(gaussian_example_fit))
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