Summary for BAMLSS — summary.bamlss • bamlss

The function takes an object of class "bamlss" and produces summaries of optimizer and sampler function outputs.

# S3 method for bamlss
summary(object, model = NULL,
  FUN = NULL, parameters = TRUE, ...)

# S3 method for summary.bamlss
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

object: An object of class "bamlss".
x: An oject of class "summary.bamlss".
model: Character or integer, specifies the model for which a summary should be computed.
FUN: Function that should be applied on samples, see also function coef.bamlss.
parameters: If an optimizer function is applied within the bamlss call, should the values of the estimated parameters be part of the summary?
digits: Controls number of digits printed in output.
...: Other arguments.

Details

If the fitted model contains samples, summaries according to the supplied function can be computed, e.g., different quantiles of samples. See also function coef.bamlss that extracts the coefficient summaries.

If an optimizer function was used within the bamlss call, estimated parameters will be included per default into the summary.

Note that summaries not based on samples can be user defined, e.g., as returned from function samplestats or the return values of optimizer function, e.g., see function opt_bfit.

Value

summary.bamlss produces the following summary:

call: The initial bamlss call.
family: The family that is used for modeling.
formula: The model formula.
model.matrix: Summary of parameteric terms.
smooth.construct: Summary of smooth terms.
model.stats: Other model statistics, e.g., as returned from optimizer functions and/or produces by function samplestats.

Examples

if (FALSE) ## Generate some data.
d <- GAMart()

## Model formula.
f <- list(
  num ~ s(x1) + s(x2),
  sigma ~ s(x3) + te(lon,lat)
)

## Estimate model.
b <- bamlss(f, data = d)
#> Error in eval(expr, envir, enclos): object 'd' not found

## Print the summary.
print(summary(b))
#> Error in eval(expr, envir, enclos): object 'b' not found