GenEnv.fun: Calculation of simulated envelopes In NHPoisson: Modelling and Validation of Non Homogeneous Poisson Processes

Description

This function calculates a point estimation and an envelope for a given statistic using a Monte Carlo approach. The statistic must be a function of the occurrence points of a NHPP.

It calls the auxiliary function funSim.fun (not intended for the users), see Details section.

Usage

 1 2 GenEnv.fun(nsim, lambda, fun.name, fun.args = NULL, clevel = 0.95, cores = 1, fixed.seed=NULL) 

Arguments

 nsim Number of simulations for the calculations. lambda Numeric vector of the intensity λ(t) (or \hat λ(t)) of the NHPP. fun.name Name of the function defining the statistic to be estimated. fun.args Additional arguments for the function fun.name. clevel Confidence level of the envelope. cores Optional. Number of cores of the computer to be used in the calculations. Default: one core is used. fixed.seed An integer or NULL. If it is an integer, that is the value used to set the seed in random generation processes. It it is NULL, a random seed is used.

Details

The auxiliary function funSim.fun generates a simulated sample of the occurrence points in a NHPP and calculates the corresponding statistic using the simulated points.

Value

A list with elements

 valmed Point estimation (mean value) of the statistic to be calculated. valinf Lower value of the simulated CI. valsup Upper value of the simulated CI. lambda Input argument. nsim Input argument. nsimval Number of valid simulations (used in the calculation of the CI and the point estimation). fixed.seed Input argument.

simNHP.fun, resQQplot.fun
  1 2 3 4 5 6 7 8 9 10 11 12 13 14 # Calculation of the point estimation and a 95% CI based on 100 simulations #for the second occurrence time of a NHPP with intensity lambdat. #posk.fun(x, k) is a function that returns the value in the row k of vector x. lambdat<-runif(1000,0.01,0.02) aux<-GenEnv.fun(lambda=lambdat,fun.name="posk.fun",fun.args=2,nsim=100) #if we want reproducible results, we can fixed the seed in the generation process #(the number of cores used in the calculations must also be the same to reproduce #the result) aux<-GenEnv.fun(lambda=lambdat,fun.name="posk.fun",fun.args=2,nsim=100,fixed.seed=123) #the result (with 1 core): Lower interval: 25.55; Mean value: 136.06; Upper interval: 288