1%feature("docstring") OT::Burr
2"Burr distribution.
3
4Available constructors:
5    Burr(*c=1.0, k=1.0*)
6
7Parameters
8----------
9c : float, :math:`c > 0`
10k : float, :math:`k > 0`
11
12Notes
13-----
14Its probability density function is defined as:
15
16.. math::
17
18    f_X(x) = c k \frac{x^{c - 1}}{(1 + x^c)^{k + 1}}, \quad x \in \Rset^{+*}
19
20with :math:`c, k > 0`.
21
22Its only, first-order moment is:
23
24.. math::
25
26    \Expect{X} = k {\rm B}(k - 1 / c, 1 + 1 / c)
27
28where :math:`\rm B` denotes Euler's beta function.
29
30Examples
31--------
32Create a distribution:
33
34>>> import openturns as ot
35>>> distribution = ot.Burr(2.0, 3.0)
36
37Draw a sample:
38
39>>> sample = distribution.getSample(5)"
40
41// ---------------------------------------------------------------------
42
43%feature("docstring") OT::Burr::getC
44"Accessor to the parameter :math:`c`.
45
46Returns
47-------
48c : float"
49
50// ---------------------------------------------------------------------
51
52%feature("docstring") OT::Burr::getK
53"Accessor to the parameter :math:`k`.
54
55Returns
56-------
57k : float"
58
59// ---------------------------------------------------------------------
60
61%feature("docstring") OT::Burr::setC
62"Accessor to the parameter :math:`c`.
63
64Parameters
65----------
66c : float, :math:`c > 0`"
67
68// ---------------------------------------------------------------------
69
70%feature("docstring") OT::Burr::setK
71"Accessor to the parameter :math:`k`.
72
73Parameters
74----------
75k : float, :math:`k > 0`"
76