covatest (version 1.0.1)

covastatM-class: Class "covastatM"

Description

A class for the sample spatio-temporal covariances for the specified spatial and temporal lags, given in stpairs (object of class couple), for the test on the type of class of models. Depending on the type of test, the empirical variance, the sample spatial and temporal marginal covariances are also computed.

Usage

covastatM(matdata, pardata1, pardata2, stpairs, typetest = "productSum",
  beta.data = NULL)
# S4 method for covastatM
show(object)

Arguments

matdata

STFDF/STSDF or data.frame; which contains the coordinates of the spatial points, the identification code of the spatial points, the indentification code of the temporal points and the values of the variable, typically output from dataprep

pardata1

integer, it represents the column in which the spatial ID is stored (if the spatio-temporal data set is given as data.frame) or the number of variables in the STFDF/STSDF (if the data are given as a STFDF/STSDF)

pardata2

integer, it represents the column in which the values of the variable are stored (if the spatio-temporal data set is given as data.frame) or the slot in which the values of the variable of interest are stored (if the data are given as a STFDF/STSDF). Note that for STFDF/STSDF the argument is set, by default, equal to 1 if the number of variables is equal to 1

stpairs

object of class couples, containing the spatial points and the corresponding temporal lags to be analyzed

typetest

character; set typetest = "productSum" for the test on the product-sum class of models (default choice), typetest = "intProduct" for the test on the integrated product class of models, typetest = "gneiting" for the test on the Gneiting class of models

beta.data

vector; this argument is required only for typetest = "gneiting", otherwise it has to be set equal to NULL (default choice). It contains the different values of the parameter beta, which can assume values in the range 0-1

object

object of class covastatM for method show

Slots

G

matrix; containing the spatio-temporal covariances for the specified lags. For all tests, the sample variance and the sample spatial and temporal marginal covariances are also computed and stored in G

cova.h

matrix; containing the sample spatial marginal covariances for the specified lags

cova.u

matrix; containing the sample temporal marginal covariances for the specified lags

f.G

array; containing the computation of specific functions of the elements of G, see references

B

matrix; containing the computation of the derivatives of each element of f.G with respect to each element of G

A

contrast matrix

beta.data

vector; containing the different values of the parameter beta, available only for the test on the Gneiting class of model (typetest = "gneiting")

typetest

character; contains the code of the test to be performed

Details

A message appears on the user's console if the G vector contains spatio-temporal negative covariances. The message returns the negative value/values and it will help to identify the spatial and the temporal lags involved.

References

Li, B., Genton, M.G., Sherman, M., 2007, A nonparametric assessment of properties of spacetime covariance functions. Journal of the American Statistical Association, 102 736--744.

De Iaco, S., Palma, M., Posa, D., 2016. A general procedure for selecting a class of fully symmetric space-time covariance functions. Environmentrics, 27(4) 212--224.

Cappello, C., De Iaco, S., Posa, D., 2018, Testing the type of non-separability and some classes of covariance models for space-time data. Stochastic Environmental Research and Risk Assessment, 32 17--35

See Also

'>couples

dataprep

Examples

# NOT RUN {
# --start define the STFDF rr_13-- #
library(sp)
library(spacetime)
library(gstat)
data(air)
ls()
if (!exists("rural")) rural = STFDF(stations, dates, data.frame(PM10 =
as.vector(air)))
rr = rural[,"2005::2010"]
unsel = which(apply(as(rr, "xts"), 2, function(x) all(is.na(x))))
r5to10 = rr[-unsel,]
rr_13 <- r5to10[c("DEHE046","DESN049","DETH026","DENW063","DETH061","DEBY047",
"DENW065","DEUB029","DENW068","DENI019","DEHE051","DERP016","DENI051"),
"2005::2006"]
# --end define the STFDF rr_13-- #

sel.staz.mod <- c("DERP016", "DENW065", "DENW063", "DEHE046", "DEUB029",
"DETH061", "DENW068", "DETH026", "DENI051")

sp.couples.in.mod <- matrix(data = c("DERP016", "DENW065", "DENW063", "DEHE046",
                                    "DEUB029", "DETH061", "DEHE046", "DENW063",
                                    "DERP016", "DENW068", "DETH026", "DENI051",
                                    "DEUB029", "DETH061", "DENI051", "DETH061",
                                    "DERP016", "DEUB029"),
                           ncol = 2, byrow = TRUE)

t.couples.in.mod <- c(1, 2, 3)

couples.mod <- couples(sel.staz = sel.staz.mod, sp.couples.in =
                        sp.couples.in.mod, t.couples.in = t.couples.in.mod,
                      typetest = "productSum", typecode = character())

zero.index <- matrix(data=c(3, 7, 6, 7, 9, 7), ncol=2, byrow = TRUE)

couples.mod <- setzero(x = couples.mod, zero = FALSE, index = zero.index, value = 0)

covast.ps <- covastatM(matdata = rr_13, pardata1 = 1, pardata2 = 1,
                       stpairs = couples.mod, typetest = "productSum", beta.data = NULL)

###method for covastat
#1. show
covast.ps

# }