# R/rtpois.R In DSsim: Distance Sampling Simulations

#### Documented in rtpois

```#' Randomly generates values from a zero-truncated Poisson distribution
#'
#' Generates values from a zero-truncated Poisson distribution with mean
#' equal to that specified. It uses a look up table to check which value of
#' lambda will give values with the requested mean.
#'
#' @param N number of values to randomly generate
#' @param mean mean of the generated values
#' @note Internal function not intended to be called by user.
#' @author Laura Marshall
#' @importFrom stats runif
#' @importFrom stats dpois
#' @importFrom stats qpois
#'
rtpois <-
function(N, mean=NA){
# Ensure it is an integer value
mean <- round(mean)
if(mean == 1){
warning("Generating from a zero truncated poisson distribution with mean = 1 will result in all values being 1.", call. = FALSE, immediate. = TRUE)
}
truncated.poisson.table <- data.frame(mean = 1:20, lambda = c(5.6469669879783e-05, 1.5936343341849, 2.82144264293862, 3.9207052500513, 4.96512876739183, 5.98490244735758, 6.99357578449238, 7.9973210436761, 8.99889023979162, 9.99954616955456, 10.9998163134426, 11.999926276307, 12.9999591161807, 14, 15, 16, 17, 18, 19, 20))
#find corresponding lambda value for desired mean
lambda <- truncated.poisson.table\$lambda[mean] #can make this just a vector rather than a dataframe
lambda <- ifelse(is.na(lambda), mean, lambda)
#generate quantiles from a uniform distribution between the probability of getting a zero, given lambda, and 1.
#endpoints are altered to ensure p is between these values and not equal to as this generates 0's or Infs.
p <- runif(N, dpois(0, lambda)+1e-10, 1-1e-10)
#find the smallest integer x such that P(X <= x) >= p
tpois <- qpois(p, lambda)
return(tpois)
}
```

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DSsim documentation built on March 26, 2020, 7:39 p.m.