Package 'burgle'

Burgle

Description

Burgling what is necessary from different objects

Usage

burgle(object, ...)

## S3 method for class 'lm'
burgle(object, ...)

## S3 method for class 'glm'
burgle(object, ...)

## S3 method for class 'CauseSpecificCox'
burgle(object, ...)

## S3 method for class 'cph'
burgle(object, ...)

## S3 method for class 'flexsurvreg'
burgle(object, ...)

## S3 method for class 'multinom'
burgle(object, ...)

## S3 method for class 'coxph'
burgle(object, ...)

Arguments

object	the model object to burgle
...	must be left empty for now

Value

a burgle_ object

Examples

fit <- lm(Sepal.Length ~ Sepal.Width + Petal.Length, data = iris)
bfit <- burgle(fit)
object.size(fit)
object.size(bfit)

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Predict for burgle methods

Description

Predict for burgle methods

Usage

## S3 method for class 'burgle_CauseSpecificCox'
predict(
  object,
  newdata = NULL,
  type = "lp",
  cause = 1,
  original = TRUE,
  draws = 1,
  sims = 1,
  times = NULL,
  ...
)

## S3 method for class 'burgle_cph'
predict(object, ...)

## S3 method for class 'burgle_flexsurvreg'
predict(
  object,
  newdata = NA,
  original = TRUE,
  draws = 1,
  sims = 1,
  type = "lp",
  times = NULL,
  ...
)

## S3 method for class 'burgle_multinom'
predict(
  object,
  newdata = NA,
  original = TRUE,
  draws = 1,
  sims = 1,
  type = "lp",
  floor = FALSE,
  seed = NULL,
  ...
)

## S3 method for class 'burgle_coxph'
predict(
  object,
  newdata = NA,
  original = TRUE,
  draws = 1,
  sims = 1,
  type = "lp",
  times = NULL,
  ...
)

## S3 method for class 'burgle_lm'
predict(
  object,
  newdata,
  original = TRUE,
  draws = 1,
  sims = 1,
  type = "lp",
  se = FALSE,
  limits = NULL,
  ...
)

## S3 method for class 'burgle_glm'
predict(
  object,
  newdata,
  original = TRUE,
  draws = 1,
  sims = 1,
  type = "lp",
  se = FALSE,
  ...
)

Arguments

object	the results of burgle_* object
newdata	new data of class data.frame
type	either 'lp', 'response', 'link' for glm or 'risk' if time dependent
cause	which cause do you want to predict
original	whether or not to predict using the original model
draws	how many different models to simulate
sims	how many simulated response to draw
times	if type = "risk" time for which to predict risk, if times and sims is multiple the return will be lists within lists
...	for future methods
floor	will set the minimum odds to 0, if negative odds exists
seed	a seed to specificy for simulating responses (multinomial only)
se	whether or not to include the standard error in the simulations
limits	limits (minimum and maximum) for simulated response values.

Value

either a matrix or list of new model predictions

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