stat_hkr {funStatTest} | R Documentation |
Horváth-Kokoszka-Reeder statistics
Description
The Horváth-Kokoszka-Reeder statistics defined in Chakraborty & Chaudhuri (2015) (and noted HKR1 and HKR2 in Smida et al 2022) are computed to compare two sets of functional trajectories.
Usage
stat_hkr(MatX, MatY)
Arguments
MatX |
numeric matrix of dimension |
MatY |
numeric matrix of dimension |
Value
A list with the following elements
-
T1
: numeric value corresponding to the HKR1 statistic value -
T2
: numeric value corresponding to the HKR2 statistic value -
eigenval
: numeric vector of eigen values from the empirical pooled covariance matrix ofMatX
andMatY
(see Smida et al, 2022, for more details)
References
Horváth, L., Kokoszka, P., & Reeder, R. (2013). Estimation of the mean of functional time series and a two-sample problem. Journal of the Royal Statistical Society. Series B (Statistical Methodology), 75(1), 103–122. doi:10.1111/j.1467-9868.2012.01032.x
Zaineb Smida, Lionel Cucala, Ali Gannoun & Ghislain Durif (2022) A median test for functional data, Journal of Nonparametric Statistics, 34:2, 520-553, doi:10.1080/10485252.2022.2064997, hal-03658578
See Also
Examples
simu_data <- simul_data(
n_point = 100, n_obs1 = 50, n_obs2 = 75, c_val = 10,
delta_shape = "constant", distrib = "normal"
)
MatX <- simu_data$mat_sample1
MatY <- simu_data$mat_sample2
stat_hkr(MatX, MatY)