Triangledf
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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).
- for function = 'quantile' - interval (0,1).
- for function = '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
See Also
betadf, cauchydf, chidf, expdf, gammadf, gumbeldf, laplacedf, logisdf, lognormdf, normdf, paretodf, raydf, unifdf, weibulldf