nhpp.sim.slow: Simulate a non-homogeneous Poisson process.

In poisson: Simulating Homogenous & Non-Homogenous Poisson Processes

Description

Get the n consecutive event times of a non-homogeneous poisson process.Events are simulated using an homogeneous process with rate, and an event at time t is admitted with probability prob.func(t).

Usage

nhpp.sim.slow(rate, num.events, prob.func, num.sims = 1, t0 = 0, prepend.t0 = T)

Arguments

rate	the rate at which events occur in the equivalent homogeneous Poisson process, aka lambda
num.events	number of event times to simulate in each process
prob.func	aka intensity function, function that takes time as sole argument and returns value between 0 and 1
num.sims	number of simulated paths to create
t0	the reference start time of all events
prepend.t0	T to include t0 at the start of the process

Details

This method is called 'thinning' by Lewis & Shedler (1978)

Value

a numeric vector of length num.events if num.sims=1 else, a num.events by num.sims matrix

Note

This item is my original (slower) implementation of NHPP simulation, hence the name. It does not use recursion so the code is easier to understand.

Author(s)

Kristian Brock - Author, Daniel Slade - Contributor

References

Lewis & Shedler, Simulation of Non-Homogeneous Poisson Processes by Thinning, 1978

See Also

nhpp.scenario, hpp.sim

Examples

intensity <- function(t) pmin(t/3, 1)
rate <- 10
num.events <- 100
nhpp.sim.slow(rate, num.events, prob.func=intensity)

Example output

  [1]  0.0000000  0.4116549  0.4655081  1.4094099  1.4488457  1.6361921
  [7]  1.6396192  1.7665498  1.8965739  1.9614692  2.5012648  2.6040403
 [13]  2.7749804  2.8038559  2.8941296  2.9089524  2.9847044  3.0030031
 [19]  3.1879452  3.2127571  3.3213756  3.4242147  3.5162812  3.5469986
 [25]  3.7125864  3.9145112  4.0947689  4.1576070  4.2067468  4.2075695
 [31]  4.2532464  4.3224989  4.4261381  4.4505781  4.4520042  4.5602001
 [37]  4.6179936  4.6682253  4.6751265  4.6924072  4.7353545  4.8109343
 [43]  4.8292302  4.8528244  4.9389766  5.1069145  5.1471498  5.1986163
 [49]  5.2906658  5.4312336  5.5938176  5.6090924  5.6120410  5.6787793
 [55]  5.6864556  5.8366333  5.8499927  5.9185221  6.1697647  6.2645798
 [61]  6.2665689  6.3464314  6.4114004  6.4412547  6.4449076  6.6721814
 [67]  6.6742618  6.9923167  7.0232604  7.0808074  7.0867798  7.1376291
 [73]  7.2405845  7.3036863  7.3259406  7.7830517  7.8662522  7.8870632
 [79]  7.9661875  8.0171238  8.0212245  8.1232042  8.2721005  8.7361643
 [85]  8.8268800  9.1334731  9.1440382  9.3562450  9.4573380  9.4975090
 [91]  9.5819067  9.7136790  9.8692218  9.9395992 10.0157435 10.0981424
 [97] 10.4266988 10.4426750 10.4637831 10.5203645 10.6345056

poisson documentation built on May 2, 2019, 6:53 a.m.