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PLS_Toolbox Documentation: betadf | < ttest2u | cauchydf > |
betadf
Purpose
Beta distribution.
Synopsis
prob = betadf(function,x,a,b,options)
Description
Estimates cumulative distribution function (cumulative, cdf), probability density function (density, pdf), quantile (inverse of cdf), or random numbers for a Beta distribution.
This distribution is commonly used to model activity time. In its usual form, the data must be in (0,1), but this toolbox will allow both a location and scale parameter (in addition to the a and b above). This may be symmetric or asymmetric.
INPUTS:
Note: If inputs (x, a, and b) 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 such values will return NaN in the results.
Options
options is a structure array with the following fields:
The default options structure can be retrieved using: options = betadf('options').
Examples
Cumulative:
>> prob = betadf('c', [0.85 0.9],1,2)
prob =
0.9775 0.9900
>> x = [0:0.01:1];
>> plot(x,betadf('c',x,1,2),'b-',x,betadf('c',x,0.5,0.5),'r-')
Density:
>> prob = betadf('d', 0.9, 1, 2)
prob =
0.2000
>> x = [0:0.01:1];
>> plot(x,betadf('d',x,1,2),'b-',x,betadf('d',x,0.5,0.5),'r-')
Quantile:
>> prob = betadf('q',[0.9775 0.9900]',1,2)
prob =
0.8500
0.9000
Random:
>> prob = betadf('r',[5 1],1,2)
prob =
0.3791
0.2549
0.8169
0.0216
0.1516
See Also
cauchydf, chidf, expdf, gammadf, gumbeldf, laplacedf, lognormdf, logisdf, normdf, paretodf, raydf, triangledf, unifdf, weibulldf
< ttest2u | cauchydf > |