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PDF, CDF and ICDF functions for other distributions + interactive graphics
08-12-2014, 09:55 AM (This post was last modified: 08-12-2014 02:20 PM by mcjtom.)
Post: #1
PDF, CDF and ICDF functions for other distributions + interactive graphics
The Prime seems to have build in PDF, CDF and ICDF functions for the following standard textbook distributions: Normal, T, Chi Sq., F, Binomial, and Poisson.

While this is great, would including a few other distributions be considered? There are many useful theoretical distributions out there, but I would think that the following standard four would add a lot of power to Prime stat's capabilities:

continuous: lognormal, exponential
discrete: hypergeometric, negative-binomial

Also, I would think that adding some easy to use graphical displays for those distributions would be of great benefit (to all users, but especially to students). Inference/Confidence Interval option already have such a display, but only for Normal and T PDF, using calculated standard error for their SD parameter.

This is pushing it, but if random numbers could be generated from each of the available distributions as well (not only Normal), that would be positively awesome.

Cheers!
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08-12-2014, 08:04 PM
Post: #2
RE: PDF, CDF and ICDF functions for other distributions + interactive graphics
You can try the following Xcas commands, if you are lucky they will be there inside the CAS, if not ask HP to add them to the lexer. For random numbers generation inside the CAS according to a distribution the command is rand (or ranv or ranm with one or two dimensions) with the distribution law and the parameters, for example
ranm(4,5,binomial,10,0.3) will generate a random matrix with coefficients distributed like the binomial distribution with parameters n=10 and p=0.3.
Cmds/Proba stats/Distributions/betad
Cmds/Proba stats/Distributions/betad_cdf
Cmds/Proba stats/Distributions/betad_icdf
Cmds/Proba stats/Distributions/binomial
Cmds/Proba stats/Distributions/binomial_cdf
Cmds/Proba stats/Distributions/binomial_icdf
Cmds/Proba stats/Distributions/cauchyd
Cmds/Proba stats/Distributions/cauchyd_cdf
Cmds/Proba stats/Distributions/cauchyd_icdf
Cmds/Proba stats/Distributions/chisquared
Cmds/Proba stats/Distributions/chisquared_cdf
Cmds/Proba stats/Distributions/chisquared_icdf
Cmds/Proba stats/Distributions/exponentiald
Cmds/Proba stats/Distributions/exponentiald_cdf
Cmds/Proba stats/Distributions/exponentiald_icdf
Cmds/Proba stats/Distributions/fisherd
Cmds/Proba stats/Distributions/fisherd_cdf
Cmds/Proba stats/Distributions/fisherd_icdf
Cmds/Proba stats/Distributions/gammad
Cmds/Proba stats/Distributions/gammad_cdf
Cmds/Proba stats/Distributions/gammad_icdf
Cmds/Proba stats/Distributions/geometric
Cmds/Proba stats/Distributions/geometric_cdf
Cmds/Proba stats/Distributions/geometric_icdf
Cmds/Proba stats/Distributions/negbinomial
Cmds/Proba stats/Distributions/negbinomial_cdf
Cmds/Proba stats/Distributions/negbinomial_icdf
Cmds/Proba stats/Distributions/normald
Cmds/Proba stats/Distributions/normald_cdf
Cmds/Proba stats/Distributions/normald_icdf
Cmds/Proba stats/Distributions/poisson
Cmds/Proba stats/Distributions/poisson_cdf
Cmds/Proba stats/Distributions/poisson_icdf
Cmds/Proba stats/Distributions/studentd
Cmds/Proba stats/Distributions/studentd_cdf
Cmds/Proba stats/Distributions/studentd_icdf
Cmds/Proba stats/Distributions/uniformd
Cmds/Proba stats/Distributions/uniformd_cdf
Cmds/Proba stats/Distributions/uniformd_icdf
Cmds/Proba stats/Distributions/weibulld
Cmds/Proba stats/Distributions/weibulld_cdf
Cmds/Proba stats/Distributions/weibulld_icdf
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