Z-residuals for Bernoulli models fitted with brms

Zresidual.bernoulli.brms() is the S3 method for Zresidual() when applied to Bernoulli (binary) regression models fitted with brms::brm() and family = bernoulli(). Objects are dispatched here when the fitted object is a "brmsfit" with family "bernoulli" and has been internally tagged with the class "bernoulli.brms" by Zresidual().

In most cases users should call Zresidual() directly on the brmsfit object, e.g. Zresidual(fit), rather than calling Zresidual.bernoulli.brms() explicitly.

Usage

# S3 method for class 'bernoulli.brms'
Zresidual(object, nrep = 1, data = NULL, type = NULL, method = "iscv", ...)

Arguments

object

A brmsfit object with brms::family(object)$family == "bernoulli".

nrep

Integer; number of replicated Z-residual sets to generate. Defaults to 1.

data

Optional data frame used for prediction. If NULL, the data stored inside the brmsfit object are used.

type

Optional character string controlling the residual type, interpreted by the underlying implementation (if used).

method

Character string specifying the residual calculation method: "iscv" for importance-sampled cross-validated randomized predictive p-values, "rpost" for randomized posterior predictive p-values, or "mpost" for middle-value posterior predictive p-values. Default is "iscv".

...

Further arguments passed to the underlying implementation

Value

A numeric matrix of Z-residuals with one column per replication, as returned by Zresidual_bernoulli_brms(), but with the class "zresid" added to its class vector.

Examples

if (FALSE) { # \dontrun{
  library(brms)
  fit_bern <- brm(y ~ x1 + x2, data = df, family = bernoulli())

  ## ISCV-based Z-residuals
  z1 <- Zresidual(fit_bern, method = "iscv", nrep = 2)

  ## Posterior predictive Z-residuals
  z2 <- Zresidual(fit_bern, method = "rpost")
} # }