Title:	Max-Type Test for Marginal Correlation with Bootstrap
Version:	1.0.1
Description:	Test the marginal correlation between a scalar response variable with a vector of explanatory variables using the max-type test with bootstrap. The test is based on the max-type statistic and its asymptotic distribution under the null hypothesis of no marginal correlation. The bootstrap procedure is used to approximate the null distribution of the test statistic. The package provides a function for performing the test. For more technical details, refer to Zhang and Laber (2014) <doi:10.1080/01621459.2015.1106403>.
License:	MIT + file LICENSE
Encoding:	UTF-8
RoxygenNote:	7.2.3
LinkingTo:	Rcpp, RcppArmadillo
Imports:	Rcpp
URL:	https://github.com/canyi-chen/MarginalMaxTest
BugReports:	https://github.com/canyi-chen/MarginalMaxTest/issues
NeedsCompilation:	yes
Packaged:	2025-04-19 17:12:18 UTC; chencanyi
Author:	Canyi Chen [aut, cre, cph]
Maintainer:	Canyi Chen <cychen.stats@outlook.com>
Repository:	CRAN
Date/Publication:	2025-04-23 09:50:04 UTC

Test for marginal effects of predictors on a scalar response

Description

Test for marginal effects of predictors on a scalar response

Usage

marginal.test(x, y, B = 199L, method = "adaptive")

Arguments

Value

A list containing the p-value and computation time

Note

This function is based on the C implementation by Zhang and Laber (2014) doi:10.1080/01621459.2015.1106403.

Examples

# Generate sample data
set.seed(47)
n <- 200
p <- 10
x <- matrix(rnorm(n*p), n, p)
y <- 0.25*x[,1] + rnorm(n)
# Run the test
marginal.test(x, y, B = 200, method = "adaptive")
marginal.test(x, y, B = 200, method = "max")
marginal.test(x, y, B = 200, method = "sum")