stationary.sePP {QRMlib}R Documentation

Stationarity of Self-Exciting Model

Description

checks a sufficient condition for stationarity of a self-exciting model and gives information about cluster size

Usage

stationary.sePP(sePP)

Arguments

sePP a fitted self-exciting process created with fit.sePP or marked self-exciting process created with fit.seMPP

Value

a vector consisting of binary flag for stationarity condition, estimated number of direct decendents of any event and estimated size of cluster generated by any new event

References

Daley and Vere-Jones, An Introduction to the Theory of Point Processes, Springer, 2nd Edition 2003, page 203

See Also

fit.sePP, fit.seMPP

Examples

data(sp500);
sp500.nreturns <- -mk.returns(sp500); 
window <- (seriesPositions(sp500.nreturns) > 
        timeDate("12/31/1995",format = "%m/%d/%Y")); 
sp500.nreturns <- sp500.nreturns[window]; 
tmp <- extremalPP(sp500.nreturns,ne=100); 
mod3a <- fit.seMPP(tmp,mark.influence=FALSE,std.errs=TRUE); 
#Note that stationary.sePP applies to both sePP and seMPP processes.
stationary.sePP(mod3a); 

[Package QRMlib version 1.4.4 Index]