triangular: The Triangular Distribution In mc2d: Tools for Two-Dimensional Monte-Carlo Simulations

Description

Density, distribution function, quantile function and random generation for the triangular distribution with minimum equal to min, mode equal mode and maximum equal to max.

Usage

 ```1 2 3 4``` ```dtriang(x, min=-1, mode=0, max=1, log=FALSE) ptriang(q, min=-1, mode=0, max=1, lower.tail=TRUE, log.p=FALSE) qtriang(p, min=-1, mode=0, max=1, lower.tail=TRUE, log.p=FALSE) rtriang(n, min=-1, mode=0, max=1) ```

Arguments

 `x,q` vector of quantiles. `p` vector of probabilities. `n` number of observations. If length(n) > 1, the length is taken to be the number required. `min` vector of minima. `mode` vector of modes. `max` vector of maxima. `log, log.p` logical; if TRUE, probabilities p are given as log(p). `lower.tail` logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x].

Details

For the case of u := min == mode == max, there is no density in that case and dtriang will return NaN (the error condition) (Similarity with dunif).

Value

dtriang gives the density, ptriang gives the distribution function, qtriang gives the quantile function, and rtriang generates random deviates.

Examples

 ```1 2 3``` ```curve(dtriang(x, min=3, mode=5, max=10), from = 2, to = 11) ##no density when min == mode == max dtriang(c(1, 2, 3), min=2, mode=2, max=2) ```

mc2d documentation built on May 31, 2017, 5:01 a.m.