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1[section:exp_dist Exponential Distribution]
2
3``#include <boost/math/distributions/exponential.hpp>``
4
5   template <class RealType = double,
6             class ``__Policy``   = ``__policy_class`` >
7   class exponential_distribution;
8
9   typedef exponential_distribution<> exponential;
10
11   template <class RealType, class ``__Policy``>
12   class exponential_distribution
13   {
14   public:
15      typedef RealType value_type;
16      typedef Policy   policy_type;
17
18      exponential_distribution(RealType lambda = 1);
19
20      RealType lambda()const;
21   };
22
23
24The [@http://en.wikipedia.org/wiki/Exponential_distribution exponential distribution]
25is a [@http://en.wikipedia.org/wiki/Probability_distribution continuous probability distribution]
26with PDF:
27
28[equation exponential_dist_ref1]
29
30It is often used to model the time between independent
31events that happen at a constant average rate.
32
33The following graph shows how the distribution changes for different
34values of the rate parameter lambda:
35
36[graph exponential_pdf]
37
38[h4 Member Functions]
39
40   exponential_distribution(RealType lambda = 1);
41
42Constructs an
43[@http://en.wikipedia.org/wiki/Exponential_distribution Exponential distribution]
44with parameter /lambda/.
45Lambda is defined as the reciprocal of the scale parameter.
46
47Requires lambda > 0, otherwise calls __domain_error.
48
49   RealType lambda()const;
50
51Accessor function returns the lambda parameter of the distribution.
52
53[h4 Non-member Accessors]
54
55All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
56that are generic to all distributions are supported: __usual_accessors.
57
58The domain of the random variable is \[0, +[infin]\].
59
60[h4 Accuracy]
61
62The exponential distribution is implemented in terms of the
63standard library functions `exp`, `log`, `log1p` and `expm1`
64and as such should have very low error rates.
65
66[h4 Implementation]
67
68In the following table [lambda] is the parameter lambda of the distribution,
69/x/ is the random variate, /p/ is the probability and /q = 1-p/.
70
71[table
72[[Function][Implementation Notes]]
73[[pdf][Using the relation: pdf = [lambda] * exp(-[lambda] * x) ]]
74[[cdf][Using the relation: p = 1 - exp(-x * [lambda]) = -expm1(-x * [lambda]) ]]
75[[cdf complement][Using the relation: q = exp(-x * [lambda]) ]]
76[[quantile][Using the relation: x = -log(1-p) / [lambda] = -log1p(-p) / [lambda]]]
77[[quantile from the complement][Using the relation: x = -log(q) / [lambda]]]
78[[mean][1/[lambda]]]
79[[standard deviation][1/[lambda]]]
80[[mode][0]]
81[[skewness][2]]
82[[kurtosis][9]]
83[[kurtosis excess][6]]
84]
85
86[h4 references]
87
88* [@http://mathworld.wolfram.com/ExponentialDistribution.html Weisstein, Eric W. "Exponential Distribution." From MathWorld--A Wolfram Web Resource]
89* [@http://documents.wolfram.com/calccenter/Functions/ListsMatrices/Statistics/ExponentialDistribution.html Wolfram Mathematica calculator]
90* [@http://www.itl.nist.gov/div898/handbook/eda/section3/eda3667.htm NIST Exploratory Data Analysis]
91* [@http://en.wikipedia.org/wiki/Exponential_distribution Wikipedia Exponential distribution]
92
93(See also the reference documentation for the related __extreme_distrib.)
94
95*
96[@http://www.worldscibooks.com/mathematics/p191.html Extreme Value Distributions, Theory and Applications
97Samuel Kotz & Saralees Nadarajah]
98discuss the relationship of the types of extreme value distributions.
99
100[endsect] [/section:exp_dist Exponential]
101
102[/ exponential.qbk
103  Copyright 2006 John Maddock and Paul A. Bristow.
104  Distributed under the Boost Software License, Version 1.0.
105  (See accompanying file LICENSE_1_0.txt or copy at
106  http://www.boost.org/LICENSE_1_0.txt).
107]
108
109