mvgam_draws function

Extract posterior draws from fitted mvgam objects

Extract posterior draws in conventional formats as data.frames, matrices, or arrays.

## S3 method for class 'mvgam'
as.data.frame(
  x,
  row.names = NULL,
  optional = TRUE,
  variable = "betas",
  use_alias = TRUE,
  regex = FALSE,
  ...
)

## S3 method for class 'mvgam'
as.matrix(x, variable = "betas", regex = FALSE, use_alias = TRUE, ...)

## S3 method for class 'mvgam'
as.array(x, variable = "betas", regex = FALSE, use_alias = TRUE, ...)

## S3 method for class 'mvgam'
as_draws(
  x,
  variable = NULL,
  regex = FALSE,
  inc_warmup = FALSE,
  use_alias = TRUE,
  ...
)

## S3 method for class 'mvgam'
as_draws_matrix(
  x,
  variable = NULL,
  regex = FALSE,
  inc_warmup = FALSE,
  use_alias = TRUE,
  ...
)

## S3 method for class 'mvgam'
as_draws_df(
  x,
  variable = NULL,
  regex = FALSE,
  inc_warmup = FALSE,
  use_alias = TRUE,
  ...
)

## S3 method for class 'mvgam'
as_draws_array(
  x,
  variable = NULL,
  regex = FALSE,
  inc_warmup = FALSE,
  use_alias = TRUE,
  ...
)

## S3 method for class 'mvgam'
as_draws_list(
  x,
  variable = NULL,
  regex = FALSE,
  inc_warmup = FALSE,
  use_alias = TRUE,
  ...
)

## S3 method for class 'mvgam'
as_draws_rvars(x, variable = NULL, regex = FALSE, inc_warmup = FALSE, ...)

Arguments

• x: list object of class mvgam

• row.names: Ignored

• optional: Ignored

• variable: A character specifying which parameters to extract. Can either be one of the following options:

  • obs_params (other parameters specific to the observation model, such as overdispsersions for negative binomial models or observation error SD for gaussian / student-t models)
  • betas (beta coefficients from the GAM observation model linear predictor; default)
  • smooth_params (smoothing parameters from the GAM observation model)
  • linpreds (estimated linear predictors on whatever link scale was used in the model)
  • trend_params (parameters governing the trend dynamics, such as AR parameters, trend SD parameters or Gaussian Process parameters)
  • trend_betas (beta coefficients from the GAM latent process model linear predictor; only available if a trend_formula was supplied in the original model)
  • trend_smooth_params (process model GAM smoothing parameters; only available if a trend_formula was supplied in the original model)
  • trend_linpreds (process model linear predictors on the identity scale; only available if a trend_formula was supplied in the original model)

  OR can be a character vector providing the variables to extract

• use_alias: Logical. If more informative names for parameters are available (i.e. for beta coefficients b or for smoothing parameters rho), replace the uninformative names with the more informative alias. Defaults to TRUE

• regex: Logical. If not using one of the prespecified options for extractions, should variable be treated as a (vector of) regular expressions? Any variable in x matching at least one of the regular expressions will be selected. Defaults to FALSE.

• ...: Ignored

• inc_warmup: Should warmup draws be included? Defaults to FALSE.

Returns

A data.frame, matrix, or array containing the posterior draws.

Examples

sim <- sim_mvgam(family = Gamma())
mod1 <- mvgam(y ~ s(season, bs = 'cc'),
             trend_model = 'AR1',
             data = sim$data_train,
             family = Gamma(),
             chains = 2,
             silent = 2)
beta_draws_df <- as.data.frame(mod1, variable = 'betas')
head(beta_draws_df)
str(beta_draws_df)

beta_draws_mat <- as.matrix(mod1, variable = 'betas')
head(beta_draws_mat)
str(beta_draws_mat)

shape_pars <- as.matrix(mod1, variable = 'shape', regex = TRUE)
head(shape_pars)