methods: S3 methods for class '"tramnet"'

In tramnet: Penalized Transformation Models

S3 methods for class "tramnet"

Description

S3 methods for class "tramnet"

Usage

## S3 method for class 'tramnet'
logLik(
  object,
  parm = coef(object, tol = 0, with_baseline = TRUE),
  w = NULL,
  newdata = NULL,
  add_penalty = FALSE,
  ...
)

## S3 method for class 'tramnet'
coef(object, with_baseline = FALSE, tol = 1e-06, ...)

## S3 method for class 'tramnet_Lm'
coef(object, with_baseline = FALSE, tol = 1e-06, as.lm = FALSE, ...)

## S3 method for class 'tramnet'
predict(object, newdata = NULL, ...)

## S3 method for class 'tramnet'
simulate(object, nsim = 1, seed = NULL, newdata = NULL, bysim = TRUE, ...)

## S3 method for class 'tramnet'
estfun(
  x,
  parm = coef(x, with_baseline = TRUE, tol = 0),
  w = NULL,
  newdata = NULL,
  ...
)

## S3 method for class 'tramnet'
residuals(
  object,
  parm = coef(object, tol = 0, with_baseline = TRUE),
  w = NULL,
  newdata = NULL,
  ...
)

## S3 method for class 'tramnet'
print(x, ...)

## S3 method for class 'tramnet'
summary(object, ...)

## S3 method for class 'summary.tramnet'
print(x, digits = max(3L, getOption("digits") - 3L), ...)

Arguments

object	Object of class "tramnet".
parm	Parameters to evaluate the log likelihood at.
w	Optional vector of sample weights.
newdata	Data to evaluate the log likelihood at.
add_penalty	Whethr or not to return the penalized log-likelihood (default add_penalty = FALSE).
...	Ignored.
with_baseline	If TRUE, also prints coefficients for the baseline transformation.
tol	Tolerance when an estimate should be considered 0 and not returned (default tol = 1e-6).
as.lm	See coef.mlt
nsim	Number of simulations, see simulate.mlt.
seed	Random seed, see simulate.mlt.
bysim	Return by simulation, see simulate.mlt.
x	Object of class "tramnet".
digits	Number of digits to print.

Value

Returns (potentially weighted w) log-likelihood based on object evaluated at parameters parm and data newdata

Numeric vector containing the model shift parameter estimates

Numeric vector containing the linear model shift parameter estimates

Vector of predictions based on object evaluated at each row of newdata

Returns a list of data.frames containing parametric bootstrap samples of the response based on the data supplied in newdata

Matrix of score contributions w.r.t. model parameters evaluated at parm

Returns a numeric vector of residuals for each row in newdata

Object of class "summary.tramnet".

Object of class "summary.tramnet".

Invisible x.

tramnet documentation built on Nov. 4, 2023, 3 p.m.