zwl {Domean} | R Documentation |
High-Dimensional Two-Sample Mean Test with Centering Adjustment
Description
Conducts a high-dimensional two-sample mean test with centering adjustment. This function is designed for cases where the number of variables \( p \) is larger than the sample sizes \( n \) and \( m \).
Usage
zwl(X, Y, order = 0)
Arguments
X |
Matrix representing the first sample (rows are observations, columns are variables). |
Y |
Matrix representing the second sample (rows are observations, columns are variables). |
order |
Integer specifying the order of centering adjustment (default is 0). |
Details
This function performs a high-dimensional two-sample mean test by adjusting the test statistic for centering. It uses a modified t-statistic and estimates the variance to handle high-dimensional data. The function also includes a custom centering adjustment based on the specified order.
Value
A list containing:
statistic |
The test statistic value. |
pvalue |
The p-value of the test. |
Tn |
The adjusted test statistic before centering. |
var |
The estimated variance. |
Examples
# Example usage:
set.seed(123)
X <- matrix(rnorm(200), nrow = 10, ncol = 20) # 10 samples, 20 variables
Y <- matrix(rnorm(200, mean = 0.5), nrow = 10, ncol = 20) # Different mean
result <- zwl(X, Y, order = 0)
print(result)
# Output:
# $statistic: The test statistic value
# $pvalue: The p-value indicating the significance of the test
# $Tn: The adjusted test statistic before centering
# $var: The estimated variance