dCount_naive_bi: Compute count probabilities using naive convolution (bi)
In GeoBosh/Countr: Flexible Univariate Count Models Based on Renewal Processes

dCount_naive_bi

R Documentation

Compute count probabilities using naive convolution (bi)

Description

Compute count probabilities using naive convolution (section 3.1) for the built-in distributions

Compute count probabilities using naive convolution (section 3.1) for the user passed survival function.

Usage

dCount_naive_bi(
  x,
  distPars,
  dist,
  nsteps = 100L,
  time = 1,
  extrap = TRUE,
  cdfout = FALSE,
  logFlag = FALSE
)

dCount_naive_user(
  x,
  distPars,
  extrapolPars,
  survR,
  nsteps = 100L,
  time = 1,
  extrap = TRUE,
  cdfout = FALSE,
  logFlag = FALSE
)

Arguments

`x`	integer (vector), the desired count values.
`distPars`	`Rcpp::List` with distribution specific slots, see details.
`dist`	character name of the built-in distribution, see details.
`nsteps`	unsiged integer number of steps used to compute the integral.
`time`	double time at wich to compute the probabilities. Set to 1 by default.
`extrap`	logical if `TRUE`, Richardson extrapolation will be applied to improve accuracy.
`cdfout`	logical if `TRUE`, the cdf will be returned instead of the count probability.
`logFlag`	logical if `TRUE` the log-probability will be returned.
`extrapolPars`	ma::vec of length 2. The extrapolation values.
`survR`	Rcpp::Function user passed survival function; should have the signature `function(t, distPars)` where `t` is a real number (>0) where the survival function is evaluated and `distPars` is a list of distribution parameters. It should return a double value.

Details

The routine does minimum number of convolution to compute the count probability P(x) sing nsteps steps, and refines result by Richardson extrapolation if extrap is TRUE using the algorithm of section 3.1.