RcppArmadillo-Functions {ECFsup} | R Documentation |
Tests for equal covariance functions problem, implemented in C++.
rcpparma_L2stat(V, sample_num, k, p, n); rcpparma_fKSCovL2(data, sample_num, k, p, n, Nsim); rcpparma_maxstat(V, sample_num, k, p, n); rcpparma_fKSCovsup(data, sample_num, k, p, n, Nsim);
V |
centered data matrix |
data |
data matrix |
sample_num |
sample sizes vector |
k |
number of groups |
p |
number of time points |
n |
total number of samples |
Nsim |
number of pseudo samples by resampling |
These are cpp versions of the tests for the ECF problem.
rcpparma_L2stat
returns a numeric value computed as the
test statistic of L2-norm test.
rcpparma_fKSCovL2
returns a double computed as the p-value of the L2-norm based test.
rcpparma_maxstat
returns a numeric value computed as the
test statistic of sup-norm test.
rcpparma_fKSCovsup
returns a double computed as the p-value of the sup-norm based test.
Bu Zhou
ZHANG (2013), GUO et al. (2016), PAPARODITIS and SAPATINAS (2016), GUO et al. (2017).
vn <- c(20,30,30); k <- length(vn); n <- sum(vn); p <- 100; Nsim <- 500; datamx <- matrix(rnorm(p*n),p,n,Nsim); rcpparma_fKSCovL2(datamx,vn,k,p,n,Nsim); rcpparma_fKSCovsup(datamx,vn,k,p,n,Nsim);