Extract Samples From a dynamitefit Object as a Data Table

Provides a data.table representation of the posterior samples of the model parameters. See as.data.frame.dynamitefit() for details.

Usage

# S3 method for dynamitefit
as.data.table(
  x,
  keep.rownames = FALSE,
  row.names = NULL,
  optional = FALSE,
  parameters = NULL,
  responses = NULL,
  types = NULL,
  summary = FALSE,
  probs = c(0.05, 0.95),
  include_fixed = TRUE,
  ...
)

Arguments

x

[dynamitefit]
The model fit object.

keep.rownames

[logical(1)]
Not used.

row.names

Ignored.

optional

Ignored.

parameters

[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.

responses

[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.

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, omega_alpha, and omega_psi. See also get_parameter_types(). Ignored if the argument parameters is supplied.

summary

[logical(1)]
If TRUE, returns posterior mean, standard deviation, and posterior quantiles (as defined by the probs argument) for all parameters. If FALSE (default), returns the posterior samples instead.

probs

[numeric()]
Quantiles of interest. Default is c(0.05, 0.95).

include_fixed

[logical(1)]
If TRUE (default), time-varying parameters for 1:fixed time points are included in the output as NA values. If FALSE, fixed time points are omitted completely from the output.

...

Ignored.

Value

A data.table containing either samples or summary statistics of the model parameters.

See also

Model outputs as.data.frame.dynamitefit(), as_draws_df.dynamitefit(), coef.dynamitefit(), confint.dynamitefit(), dynamite(), get_code(), get_data(), get_parameter_dims(), get_parameter_names(), get_parameter_types(), ndraws.dynamitefit(), nobs.dynamitefit()

Examples

data.table::setDTthreads(1) # For CRAN
as.data.table(
  gaussian_example_fit,
  responses = "y",
  types = "beta",
  summary = FALSE
)
#>      parameter    value  time category group response   type .draw .iteration
#>         <char>    <num> <int>   <char> <int>   <char> <char> <int>      <int>
#>   1:  beta_y_z 1.971788    NA     <NA>    NA        y   beta     1          1
#>   2:  beta_y_z 1.956853    NA     <NA>    NA        y   beta     2          2
#>   3:  beta_y_z 1.953325    NA     <NA>    NA        y   beta     3          3
#>   4:  beta_y_z 1.962095    NA     <NA>    NA        y   beta     4          4
#>   5:  beta_y_z 1.967552    NA     <NA>    NA        y   beta     5          5
#>  ---                                                                         
#> 196:  beta_y_z 1.960357    NA     <NA>    NA        y   beta   196         96
#> 197:  beta_y_z 1.967019    NA     <NA>    NA        y   beta   197         97
#> 198:  beta_y_z 1.968887    NA     <NA>    NA        y   beta   198         98
#> 199:  beta_y_z 1.960676    NA     <NA>    NA        y   beta   199         99
#> 200:  beta_y_z 1.961960    NA     <NA>    NA        y   beta   200        100
#>      .chain
#>       <int>
#>   1:      1
#>   2:      1
#>   3:      1
#>   4:      1
#>   5:      1
#>  ---       
#> 196:      2
#> 197:      2
#> 198:      2
#> 199:      2
#> 200:      2