PDF, CDF and ICDF functions for other distributions + interactive graphics

08122014, 09:55 AM
(This post was last modified: 08122014 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, negativebinomial 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! 

08122014, 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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