simclbin {crossrun}

Simulation of Independent Bernoulli Observations

Description

Simulation of a sequence of independent Bernoulli Observations. To reduce the amount of random draws, each simulation is based on a sequence of standard normal variables, and whether each observation is above a shift defined by the binomial probabilities assumed.

Usage

simclbin(nser = 100, nsim = 1e+05, probs = c(0.5, 0.6, 0.7, 0.8, 0.9))

Arguments

nser

length of sequence simulated

nsim

number of simulations

probs

binomial probabilites

Value

a data frame with the number of crossings and longest run for each probability. For instance the variables nc0.5 and lr0.5 are the number of crossings and the longest run for success probability 0.5. One row for each simulation.

Examples

cl30simbin <- simclbin(nser=30, nsim=100)
mean(cl30simbin$nc0.5) # mean number of crossings, p=0.5
mean(cl30simbin$lr0.9) # mean longest run, p=0.9