DiffBetaNB {betaNB} R Documentation

## Estimate Differences of Standardized Slopes and Generate the Corresponding Sampling Distribution Using Nonparametric Bootstrapping

### Description

Estimate Differences of Standardized Slopes and Generate the Corresponding Sampling Distribution Using Nonparametric Bootstrapping

### Usage

DiffBetaNB(object, alpha = c(0.05, 0.01, 0.001))

### Arguments

 object Object of class nb, that is, the output of the NB() function. alpha Numeric vector. Significance level \alpha.

### Details

The vector of differences of standardized regression slopes is estimated from bootstrap samples. Confidence intervals are generated by obtaining percentiles corresponding to 100(1 - \alpha)\% from the generated sampling distribution of differences of standardized regression slopes, where \alpha is the significance level.

### Value

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

call

Function call.

args

Function arguments.

thetahatstar

Sampling distribution of differences of standardized regression slopes.

vcov

Sampling variance-covariance matrix of differences of standardized regression slopes.

est

Vector of estimated differences of standardized regression slopes.

fun

Function used ("DiffBetaNB").

### Author(s)

Ivan Jacob Agaloos Pesigan

Other Beta Nonparametric Bootstrap Functions: BetaNB(), DeltaRSqNB(), NB(), 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., 5000L for actual research
seed = 0508
)

# DiffBetaNB ---------------------------------------------------------------
out <- DiffBetaNB(nb, alpha = 0.05)

## Methods -----------------------------------------------------------------
print(out)
summary(out)
coef(out)
vcov(out)
confint(out, level = 0.95)

[Package betaNB version 1.0.2 Index]