tvgeom_nimble: The Time-Varying (Right-Truncated) Geometric Distribution in...
In vlandau/tempo: Temporally-Explicit Models for Phenological Observations

Description Usage Arguments Details

Density (dtvgeom_nimble), distribution function (qtvgeom_nimble), quantile function (ptvgeom_nimble), and random number generation (rtvgeom_nimble for the time-varying, right-truncated geometric distribution with parameter prob. This distribution is identical to the one in the tvgeom package, but functions are implemented as nimbleFunctions, which allows them to be compiled to C++. For general use of the tvgeom distribution, it is recommended that you use the functions provided in the tvgeom package.

dtvgeom_nimble(x, prob, log = 0)

ptvgeom_nimble(q, prob, lower.tail = 1, log.p = 0)

qtvgeom_nimble(p, prob, lower.tail = 1, log.p = 0)

rtvgeom_nimble(n, prob)

`x, q`	vector of quantiles representing the trial at which the first success occurred.
`prob`	vector of the probability of success for each trial.
`log, log.p`	logical; if `TRUE`, probabilities, p, are given as `log(p)`. Defaults to `FALSE`.
`lower.tail`	logical; if `FALSE`, `ptvgeom_nimble` returns P(X > x) instead of P(X ≤ x). Defaults to `TRUE`.
`p`	vector of probabilities at which to evaluate the quantile function.
`n`	number of observations to sample. For *tvgeom_nimble functions, must be 1.

The time-varying geometric distribution describes the number of independent Bernoulli trials needed to obtain one success. The probability of success, prob, may vary for each trial. It has mass

p(x) = prob[x] * prod(1 - prob[1:(x-1)])

with support x = 1, 2, ..., n. For i in prob, 0 ≤ i ≤ 1.

vlandau/tempo documentation built on March 18, 2020, 12:04 a.m.