[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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