patest: Park-Ayyala test statistic

In MethylCapSig: Detection of Differentially Methylated Regions using MethylCap-Seq Data

Description

Calculates the two sample Park-Ayyala test statistic and p-value.

Usage

patest(X, Y)

Arguments

X	A matrix of dimension n \times k whose rows represent the samples collected from n (≥q 4) individuals from the first group on k variates.
Y	A matrix of dimension m \times k whose rows correspond to samples collected from m (≥q 4) individuals from the second group on k variates. Default value is null. If not specified, the function performs a one-sample test using X.

Details

The Park-Ayyala test statistic is used to test equality of mean vectors for two groups of multivariate observations, where the dimension is greater than the sample size. patest takes matrices X and Y as arguments whose rows represent samples from two groups respectively. Depending on the values in X and Y, the function initially determines whether to perform a one sample test (∑_{i,j} X_{i,j}^2 = 0 or ∑_{i,j} Y_{i,j}^2 = 0) or a two-sample test. The appropriate test statistic is then calculated and is returned along with the p-value which is calculated using right-tailed normal distribution.

Note: The Park-Ayyala test statistic involves repeated computation of the covariance matrix, requiring at least four samples in both the groups. See Park and Ayyala (2013) for more details.

Value

A 2 \times 1 vector consisting of the test statistic and the p-value.

Author(s)

Deepak N. Ayyala, Javkhlan-Ochir Ganbat.

References

Park, J. and Ayyala, D. N. (2013) A test for the mean vector in large dimension and small samples, Journal of Statistical Planning and Inference, 143, 929 – 943.

Examples

data(diffMethylData)
patest(diffMethylData$region1.x, diffMethylData$region1.y)
# patest(diffMethylData$region2.x, diffMethylData$region2.y)

MethylCapSig documentation built on May 2, 2019, 9:24 a.m.