| Type: | Package |
| Title: | Two-Sample Test of many Functional Means using the Energy Method |
| Version: | 1.1 |
| Date: | 2025-04-09 |
| Maintainer: | David Colin Decker <d.colin.decker@gmail.com> |
| Description: | Given two samples of size n_1 and n_2 from a data set where each sample consists of K functional observations (channels), each recorded on T grid points, the function energy method implements a hypothesis test of equality of channel-wise mean at each channel using the bootstrapped distribution of maximum energy to control family wise error. The function energy_method_complex accomodates complex valued functional observations. |
| License: | GPL-3 |
| Imports: | Rcpp (≥ 1.0.14) |
| LinkingTo: | Rcpp, RcppArmadillo |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | yes |
| Packaged: | 2025-04-19 22:25:48 UTC; David |
| Author: | David Colin Decker [aut, cre] |
| Repository: | CRAN |
| Date/Publication: | 2025-04-20 01:22:10 UTC |
Implements the two sample paired or independent energy method
Description
This function takes two samples of high-dimensional functional data, implements the energy method, and returns a p-value for the global test of equality of mean and a channel-wise p-value for each functional coordinate.
Usage
energy_method(sample_1, sample_2, num_bootstrap_reps, seed, type)
Arguments
sample_1 |
A three dimensional array with dimension attribute (K,T,n_1) where K is the number of channels, T is the number of functional recordings, and n_1 is the sample size. |
sample_2 |
A three dimensional array with dimension attribute (K,T,n_1) where K is the number of channels, T is the number of functional recordings, and n_2 is the sample size. |
num_bootstrap_reps |
A number. The number of bootstrap resamples to use when implementing the test |
seed |
A number. The seed used for randomness in bootstrap procedure |
type |
A sting. Either "paired" or "independent"" |
Value
A list containg the p-values of the test for the global hypothesis and channel-wise hypotheses, as well as summary information about the samples.
Author(s)
David Colin Decker
References
Article on energy method forthcoming
Examples
K=10
T=100
n_1=10
n_2=20
sample_1 = array(rnorm (K*T*n_1), dim=c(K, T, n_1))
sample_2 = array(rnorm (K*T*n_2), dim=c(K, T, n_2))
energy_method(sample_1, sample_2, num_bootstrap_reps=1000, seed=123, type="independent")
Implements the two sample paired or independent energy method
Description
This function takes two samples of complex-valued high-dimensional functional data, implements the energy method, and returns a p-value for the global test of equality of mean and a channel-wise p-value for each functional coordinate.
Usage
energy_method_complex(sample_1, sample_2, num_bootstrap_reps, seed, type)
Arguments
sample_1 |
A three dimensional complex array with dimension attribute (K,T,n_1) where K is the number of channels, T is the number of functional recordings, and n_1 is the sample size. |
sample_2 |
A three dimensional complex array with dimension attribute (K,T,n_1) where K is the number of channels, T is the number of functional recordings, and n_2 is the sample size. |
num_bootstrap_reps |
A number. The number of bootstrap resamples to use when implementing the test |
seed |
A number. The seed used for randomness in bootstrap procedure |
type |
A sting. Either "paired" or "independent"" |
Value
A list containg the p-values of the test for the global hypothesis and channel-wise hypotheses, as well as summary information about the samples.
Author(s)
David Colin Decker
References
Article on energy method forthcoming
Examples
K=10
T=100
n_1=10
n_2=20
sample_1_real=array(rnorm(K*T*n_1), dim=c(K,T,n_1))
sample_1_complex=array(rnorm(K*T*n_1), dim=c(K,T,n_1))
sample_1<-array(complex(real=sample_1_real, imaginary=sample_1_complex), dim=c(K,T,n_1))
sample_2_real=array(rnorm(K*T*n_2), dim=c(K,T,n_2))
sample_2_complex=array(rnorm(K*T*n_2), dim=c(K,T,n_2))
sample_2<-array(complex(real=sample_2_real, imaginary=sample_2_complex), dim=c(K,T,n_2))
energy_method_complex(sample_1, sample_2, num_bootstrap_reps=1000, seed=123, type="independent")
Energy Method
Description
Given two samples from a multi-channel functional distribtution, this package implements the energy method to perform a test of equality of mean. It returns channel-wise p-values and the global p-value.
Author(s)
David Colin Decker d.colin.decker@gmail.com