spte_decor {SpTe2M} | R Documentation |
Decorrelate the spatio-temporal data
Description
The function spte_decor
uses the estimated spatio-temporal mean and
covariance to decorrelate the observed spatio-temporal data. After data
decorrelation, each decorrelated observation should have asymptotic mean of
0 and asymptotic variance of 1, and the decorrelated data should be
asymptotically uncorrelated with each other.
Usage
spte_decor(y, st, y0, st0, T = 1, ht = NULL, hs = NULL, gt = NULL, gs = NULL)
Arguments
y |
A vector of |
st |
A three-column matrix specifying the spatial locations and observation times of the observations to decorrelate. |
y0 |
A vector of |
st0 |
A three-column matrix specifying the spatial locations and times for all
the spatio-temporal observations in |
T |
The period of the spatio-temporal mean and covariance. Default value is 1. |
ht |
The temporal kernel bandwidth |
hs |
The spatial kernel bandwidth |
gt |
The temporal kernel bandwidth |
gs |
The spatial kernel bandwidth |
Value
st |
Same as the one in the arguments. |
std.res |
The decorrelated data. |
Author(s)
Kai Yang kayang@mcw.edu and Peihua Qiu
References
Yang, K. and Qiu, P. (2020). Online Sequential Monitoring of Spatio-Temporal Disease Incidence Rates. IISE Transactions, 52, 1218-1233.
Examples
library(SpTe2M)
data(sim_dat)
y <- sim_dat$y; st <- sim_dat$st
ids <- 1:500; y.sub <- y[ids]; st.sub <- st[ids,]
decor <- spte_decor(y.sub,st.sub,y0=y.sub,st0=st.sub)