Package 'uni.shrinkage'

Title: Shrinkage Estimation for Univariate Normal Mean
Description: Implement a shrinkage estimation for the univariate normal mean based on a preliminary test (pretest) estimator. This package also provides the confidence interval based on pivoting the cumulative density function. The methodologies are published in Taketomi et al.(2024) <doi:10.1007/s42081-023-00221-2> and Taketomi et al.(2024-)(under review).
Authors: Nanami Taketomi [aut, cre], Jia-Han Shih [aut], Takeshi Emura [aut]
Maintainer: Nanami Taketomi <[email protected]>
License: GPL-2
Version: 1.0.0
Built: 2024-12-10 06:30:16 UTC
Source: CRAN

Help Index

Shrinkage Estimation for the Univariate Normal Mean based on a Preliminary Test Estimator

Description

This function computes a preliminary test (pretest) estimate for the univariate normal mean. This function also computes the confidence interval based on a pretest estimator.

Usage

uni.pt(y,s,alpha=0.05,gamma=0.05,gamma1=NA,gamma2=NA,conf.int=TRUE)

Arguments

y

A vector of normal distributed data
s

Standard deviation of y
alpha

Significance level for the preliminary hypothesis test. This parameter satisfies 0< alpha <1. The default is alpha=0.05.
gamma

A constant that 1-gamma is the confidence level. This constant satisfies 0< gamma <1. The default is gamma=0.05.
gamma1

A constant for the 1-gamma confidence level that satisfies gamma1+gamma2=gamma. This argument is optional.
gamma2

A constant for the 1-gamma confidence level that satisfies gamma1+gamma2=gamma. This argument is optional.
conf.int

An indicator whether confidence interval is in the output or not. The default is conf.int=TRUE

Value

Sample_mean

Sample mean of y
PT

Pretest estimator for the normal mean based on y
Lower.pivotCI

Lower limit of the confidence interval
Upper.pivotCI

Upper limit of the confidence interval

Author(s)

Nanami Taketomi, Takeshi Emura

References

Taketomi N, Shih JH, Emura T.(2024-). Confidence interval for the univariate normal mean based on a pretest estimator.(under review)

Examples

mu=0
s=10
y=rnorm(20,mu,s)
uni.pt(y,s)

mu=1.5
s=10
y=rnorm(20,mu,s)
uni.pt(y,s,alpha=0.10)