[SciPy-user] random variates

Travis E. Oliphant oliphant at ee.byu.edu
Fri Apr 2 18:58:18 CST 2004


Brian Gue wrote:
> Hi,
> 
> Are there examples of usage of the statistics functions? I'm 
> specifically looking for samples using scipy.stats.truncnorm and 
> scipy.stats.triang.
> 

The help should be better now.

ie.

scipy.info(scipy.stats.triang)

Basically,


 >>> info(stats.triang)
Instance of class:  triang_gen

  triang(*args, **kwds)

Triangular Distribution

     up-sloping line from loc to (loc + c*scale) and then downsloping
     for (loc + c*scale) to (loc+scale).

     standard form is in range [0,1] with c the mode
     location parameter shifts the start to loc
     scale changes the width from 1 to scale


Triangular distribution

     up-sloping line from loc to (loc + c*scale) and then downsloping
     for (loc + c*scale) to (loc+scale).

     - standard form is in the range [0,1] with c the mode.
     - location parameter shifts the start to loc
     - scale changes the width from 1 to scale


Docstring still needs work here.  Note that stats.triang  has all the 
methods of stats.truncnorm  as well (just enter c instead of a,b)

stats.triang.pdf
stats.triang.rvs

etc.







 >>> info(stats.truncnorm)
Instance of class:  truncnorm_gen

  truncnorm(*args, **kwds)

A truncated normal continuous random variable.

     Continuous random variables are defined from a standard form chosen
     for simplicity of representation.  The standard form may require
     some shape parameters to complete its specification.  The distributions
     also take optional location and scale parameters using loc= and scale=
     keywords (defaults: loc=0, scale=1)

     These shape, scale, and location parameters can be passed to any of the
     methods of the RV object such as the following:

     truncnorm.rvs(a,b,loc=0,scale=1)
         - random variates

     truncnorm.pdf(x,a,b,loc=0,scale=1)
         - probability density function

     truncnorm.cdf(x,a,b,loc=0,scale=1)
         - cumulative density function

     truncnorm.sf(x,a,b,loc=0,scale=1)
         - survival function (1-cdf --- sometimes more accurate)

     truncnorm.ppf(q,a,b,loc=0,scale=1)
         - percent point function (inverse of cdf --- percentiles)

     truncnorm.isf(q,a,b,loc=0,scale=1)
         - inverse survival function (inverse of sf)

     truncnorm.stats(a,b,loc=0,scale=1,moments='mv')
         - mean('m'), variance('v'), skew('s'), and/or kurtosis('k')

     truncnorm.entropy(a,b,loc=0,scale=1)
         - (differential) entropy of the RV.

     Alternatively, the object may be called (as a function) to fix
        the shape, location, and scale parameters returning a
        "frozen" continuous RV object:

     myrv = truncnorm(a,b,loc=0,scale=1)
         - frozen RV object with the same methods but holding the
             given shape, location, and scale fixed


Truncated Normal distribution



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