/usr/include/openturns/swig/MaximumDistribution_doc.i is in libopenturns-dev 1.9-5.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | %feature("docstring") OT::MaximumDistribution
"Maximum distribution.
Available constructors:
MaximumDistribution(*distribution*)
MaximumDistribution(*collection*)
MaximumDistribution(*distribution, size*)
Parameters
----------
distribution : :class:`~openturns.Distribution`
The underlying distribution.
collection : sequence of :class:`~openturns.Distribution`
A collection of pdfs.
size : int
Number of instances of distribution.
Notes
-----
The maximum distribution of F is the distribution of :math:`X = max(X_1, ... , X_n)`
where :math:`(X_1, ... , X_n) \\\\sim F`
.. math::
\\\\Prob{X\\\\leq x}=\\\\Prob{X_1\\\\leq x,\\\\dots,X_n\\\\leq x}
This simplifies to :math:`\\\\Prob{X\\\\leq x}=\\\\prod_{i=1}^n F_i(x)`
when :math:`X_1,\\\\dots,X_n` are independent (second constructor) and finally
it simplifies into :math:`F^n(x)` when the random variables are iid (third
constructor).
Examples
--------
Create a distribution:
>>> import openturns as ot
>>> coll = [ot.Uniform(-1.0, 1.0), ot.LogUniform(1.0, 1.2), ot.Triangular(3.0, 4.0, 5.0)]
>>> distribution = ot.MaximumDistribution(coll)
Draw a sample:
>>> sample = distribution.getSample(5)"
// ---------------------------------------------------------------------
%feature("docstring") OT::MaximumDistribution::getDistribution
"Accessor to the underlying distribution.
Returns
-------
distribution : :class:`~openturns.Distribution`
The underlying distribution."
// ---------------------------------------------------------------------
%feature("docstring") OT::MaximumDistribution::setDistribution
"Accessor to the underlying distribution.
Parameters
----------
distribution : :class:`~openturns.Distribution`
The underlying distribution."
// ---------------------------------------------------------------------
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