S3 methods {DBR}

Summary, print, plot and coef methods for Discretised Beta Regression Fits

Description

Summary, print, plot and coef methods for Discretised Beta Regression Fits

Usage

## S3 method for class 'dbr'
coef(
  object
  , prob = c(0.025, 0.5, 0.975)
  , ...
)
## S3 method for class 'dbr'
print(
  x
  , ...
)
## S3 method for class 'dbr'
summary(
  object
  , context
  , make_plot = TRUE
  , ...
)
## S3 method for class 'dbr'
plot(x, ...)

Arguments

object

Result of call to dbr.

x

Result of call to dbr.

prob

Vector of probabilities at which to calculate the posterior quantiles of model parameters.

make_plot

Whether to generate the context-dependent plots in the summary method.

context

Dataframe with a single row, containing all columns needed for prediction. These values are used for producing pseudo-coefficient plots in the summary method.

...

Further arguments passed to the functions.

Value

For coef, a 2D array of size length(prob) x nVar, where nVar is the number of model parameters. The latter itself is composed of left and right buffers, precision parameter of beta distribution, and covariate coefficients. Note that if left and/or right buffers were not estimated by dbr, their confidence interval will be identical to the point estimate. The print method prints the formula used to call dbr.

Author(s)

Mansour T.A. Sharabiani, Alireza S. Mahani

Examples

library("DBR")
data("pain")
est <- dbr(
  interference ~ severity + age
  , pain
  , control = dbr.control(
    nsmp = 50
    , nburnin = 25
  )
)
print(est)
plot(est)
coef(est, prob = c(0.05, 0.5, 0.95))
summary(est, context = pain[2, ])