NB {betaNB}

Generate the Sampling Distribution of Sample Covariances Using Nonparametric Bootstrapping

Description

Generate the Sampling Distribution of Sample Covariances Using Nonparametric Bootstrapping

Usage

NB(object, R = 5000L, seed = NULL)

Arguments

object

Object of class lm.

R

Positive integer. Number of bootstrap replications.

seed

Integer. Seed number for reproducibility.

Value

Returns an object of class nb which is a list with the following elements:

call

Function call.

args

Function arguments.

lm_process

Processed lm object.

thetahatstar

Sampling distribution of sample covariances.

jackknife

Jackknife estimates.

Author(s)

Ivan Jacob Agaloos Pesigan

References

Efron, B., & Tibshirani, R. J. (1993) An introduction to the bootstrap. Chapman & Hall.

See Also

Other Beta Nonparametric Bootstrap Functions: BetaNB(), DeltaRSqNB(), DiffBetaNB(), PCorNB(), RSqNB(), SCorNB()

Examples

# Data ---------------------------------------------------------------------
data("nas1982", package = "betaNB")

# Fit Model in lm ----------------------------------------------------------
object <- lm(QUALITY ~ NARTIC + PCTGRT + PCTSUPP, data = nas1982)

# NB -----------------------------------------------------------------------
nb <- NB(
  object,
  R = 100, # use a large value e.g., 20000L for actual research
  seed = 0508
)
nb
# The `nb` object can be passed as the first argument
# to the following functions
#   - BetaNB
#   - DeltaRSqNB
#   - DiffBetaNB
#   - PCorNB
#   - RSqNB
#   - SCorNB