CPSPpoints {IndTestPP}

Identifying the occurrence points of the indicator processes in a CPSP

Description

It calculates the occurrence points in the three indicator processes of a bivariate Common Poisson Shock Process (CPSP), using as input the two marginal processes N_1 and N_2.

Usage

CPSPpoints(N1,N2,date=NULL, dplot=T, pmfrow=c(2,1), axispoints=NULL,...)

Arguments

N1

Binary vector of the first CPSP marginal process; occurrence points must be marked with 1 and the other with 0.

N2

Binary vector of the second CPSP marginal process; occurrence points must be marked with 1 and the other with 0.

date

Optional. A vector or matrix indicating the date of each observation.

dplot

Optional. A logical flag. If it is TRUE, the marginal and indicator processes are plotted.

pmfrow

Optional. A vector of the form (nr, nc) to be supplied as value of the argument mfrow in par.

axispoints

Optional. Numeric vector with the points in the time index where axis ticks and labels (from the first column in date) have to be drawn.

...

Further arguments to be passed to the function plot.

Details

A bivariate CPSP N is usually specified by its two marginal, and possibly dependent, processes N_1 and N_2, which are the observed processes. However, N can be decomposed into three independent indicator processes: N_{(1)}, N_{(2)} and N_{(12)}, which are the processes of the points occurring only in the first marginal process, only in the second and in both of them (simultaneous points). The union of N_{(1)} and N_{(12)}, and N_{(2)} and N_{(12)} gives respectively the two marginal processes.

The points in the marginal N_{1}, N_{2} and indicator N_{(1)}, N_{(2)} and N_{(12)} processes can be optionally plotted. If date is NULL, default axis are used. Otherwise, the values in axispoints are used as the points in the time index where axis ticks and labels, from the first column in date, have to be drawn. If axispoints is NULL, a default grid of points is built using the function marca.

Value

A list with components

Px1

Vector of the occurrence points in N_{(1)}.

Px2

Vector of the occurrence points in N_{(2)}.

Px12

Vector of the occurrence points in N_{(12)}.

N1

Input argument.

N2

Input argument.

date

Input argument.

References

Abaurrea, J. Asin, J. and Cebrian, A.C. (2015). A Bootstrap Test of Independence Between Three Temporal Nonhomogeneous Poisson Processes and its Application to Heat Wave Modeling. Environmental and Ecological Statistics, 22(1), 127-144.

See Also

CPSPPOTevents, PlotMCPSP, PlotICPSP

Examples

set.seed(123)
X<-as.numeric(runif(100)<0.10)
set.seed(124)
Y<-as.numeric(runif(100)<0.15)

aux<-CPSPpoints(N1=X,N2=Y)