In bertcarnell/triangle: Distribution Functions and Parameter Estimates for the Triangle Distribution

© Copyright 2024 Robert Carnell

require(knitr)
require(triangle)
knitr::opts_chunk$set(fig.path = "man/figures/")

triangle

An R package to work with the triangle distribution and logarithmic triangle distribution

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See the package documentation here:

Getting Started

Install the R package:

# Stable CRAN version
install.packages("triangle")

# OR development version from GitHub
require(devtools)
devtools::install_github("bertcarnell/triangle")

use the functions:

• a = minimum
• b = maximum
• c = mode

require(triangle)

Triangle distribution

# rtriangle(n, a, b, c)
set.seed(42)
rtriangle(5, 1, 5, 2)

# ptriangle(x, a, b, c)
ptriangle(0:5, 0, 10, 5)

# qtriangle(p, a, b, c)
qtriangle(seq(0, 1, by = 0.2), 1, 10, 3)

# dtriangle(x, a, b, c)
dtriangle(0:4, 0, 10, 5)

Logarithmic triangle distribution

# rltriangle(n, a, b, c, logbase)
set.seed(2001)
rltriangle(5, 1, 100, 10)

# pltriangle(x, a, b, c, logbase)
pltriangle(10^(0:3), 1, 1000, 10)

# qltriangle(p, a, b, c, logbase)
qltriangle(seq(0, 1, by = 0.2), 1, 100, 20)

# dltriangle(x, a, b, c, logbase)
dltriangle(0:5, 1, 10, 5)

Parameter estimates

triangle method of moments estimates

x <- rtriangle(20, 0, 2, 1.5)
triangle_mom(x)

triangle maximum likelihood estimates

x <- c(0.1, 0.25, 0.3, 0.4, 0.45, 0.6, 0.75, 0.8)
# triangle_mle(x, debug = FALSE, maxiter = 100)
triangle_mle(x)

# standard triangle (0,1) likelihood estimates
standard_triangle_mle(x)

set.seed(1976)
x <- rtriangle(100, 1, 5, 3.5)
triangle_mle(x)

bertcarnell/triangle documentation built on July 4, 2025, 12:41 a.m.