coefboot.pffr: Simple bootstrap CIs for pffr

Description Usage Arguments Value Author(s)

View source: R/pffr-robust.R

Description

This function resamples observations in the data set to obtain approximate CIs for different terms and coefficient functions that correct for the effects of dependency and heteroskedasticity of the residuals along the index of the functional response, i.e., it aims for correct inference if the residuals along the index of the functional response are not i.i.d.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
coefboot.pffr(
  object,
  n1 = 100,
  n2 = 40,
  n3 = 20,
  B = 100,
  ncpus = getOption("boot.ncpus", 1),
  parallel = c("no", "multicore", "snow"),
  cl = NULL,
  conf = c(0.9, 0.95),
  type = "percent",
  method = c("resample", "residual", "residual.c"),
  showProgress = TRUE,
  ...
)

Arguments

object

a fitted pffr-model

n1

see coef.pffr

n2

see coef.pffr

n3

see coef.pffr

B

number of bootstrap replicates, defaults to (a measly) 100

ncpus

see boot. Defaults to getOption("boot.ncpus", 1L) (like boot).

parallel

see boot

cl

see boot

conf

desired levels of bootstrap CIs, defaults to 0.90 and 0.95

type

type of bootstrap interval, see boot.ci. Defaults to "percent" for percentile-based CIs.

method

either "resample" (default) to resample response trajectories, or "residual" to resample responses as fitted values plus residual trajectories or "residual.c" to resample responses as fitted values plus residual trajectories that are centered at zero for each gridpoint.

showProgress

TRUE/FALSE

...

not used

Value

a list with similar structure as the return value of coef.pffr, containing the original point estimates of the various terms along with their bootstrap CIs.

Author(s)

Fabian Scheipl


refund documentation built on July 1, 2021, 9:06 a.m.