triangledf Documentation


PLS_Toolbox Documentation: triangledf	< tdf	unifdf >

triangledf

Purpose

Triangle distribution.

Synopsis

prob = triangledf(function,x,a,b,c)

Description

Estimates cumulative distribution function (cumulative, cdf), probability density function (density, pdf), quantile (inverse of cdf), or random numbers for a Triangle distribution.

This distribution is usually used for rough models of data and is triangular in shape (hence the name).

INPUTS:

function = [ {'cumulative'} | 'density' | 'quantile' | 'random' ], defines the functionality to be used. Note that the function recognizes the first letter of each string so that the string could be: [ 'c' | 'd' | 'q' | 'r' ].

x = matrix in which the sample data is stored (-inf,inf).

quantile - interval (0,1).

random - vector indicating the size of the random matrix to create.

a = "min" parameter (real, <= mode).

b = "max" parameter (real, >= mode).

c = "mode" parameter (real, >= min and <=max).

Note: If inputs (x, a, b, and c) are not equal in size, the function will attempt to resize all inputs to the largest input using the RESIZE function.

Note: Functions will typically allow input values outside of the acceptable range to be passed but will convert them to NaN.

Examples

Cumulative:

>> prob = triangledf('c',2,1,3,2)

prob =

0.5000

>> x = [0:0.1:10];

>> plot(x,triangledf('c',x,1,3,2),'b-',x,triangledf('c',x,1,5,3),'r-')

Density:

>> prob = triangledf('d',2,1,3,2)

prob =

1.0000

>> x = [0:0.1:10];

>> plot(x,triangledf('d',x,0,3,0),'b-',x,triangledf('d',x,1,3,2),'r-')

Quantile:

>> prob = triangledf('q',0.5,1,3,2)

prob =

2.0000

Random:

>> prob = triangledf('r',[4 1],1,3,2)

ans =

2.2817

1.9431

2.1094

2.2585