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2. Exponential distribution - Wikipedia

   en.wikipedia.org/wiki/Exponential_distribution

   In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate; the distance parameter could be any meaningful mono-dimensional measure of the process, such as time ...

3. File:Exponential distribution pdf - public domain.svg - Wikipedia

   en.wikipedia.org/wiki/File:Exponential...

   This file contains additional information, probably added from the digital camera or scanner used to create or digitize it. If the file has been modified from its original state, some details may not fully reflect the modified file.

4. Category:Exponential family distributions - Wikipedia

   en.wikipedia.org/wiki/Category:Exponential...

   Download as PDF; Printable version; In other projects Wikidata item; Appearance. move to sidebar hide. Help ... Kaniadakis exponential distribution;

5. List of exponential topics - Wikipedia

   en.wikipedia.org/wiki/List_of_exponential_topics

   Exponential (disambiguation) Exponential backoff; Exponential decay; Exponential dichotomy; Exponential discounting; Exponential diophantine equation; Exponential dispersion model; Exponential distribution; Exponential error; Exponential factorial; Exponential family; Exponential field; Exponential formula; Exponential function; Exponential ...

6. Exponential dispersion model - Wikipedia

   en.wikipedia.org/wiki/Exponential_dispersion_model

   In the univariate case, a real-valued random variable belongs to the additive exponential dispersion model with canonical parameter and index parameter , (,), if its probability density function can be written as

7. Estimating equations - Wikipedia

   en.wikipedia.org/wiki/Estimating_equations

   Consider the problem of estimating the rate parameter, λ of the exponential distribution which has the probability density function: (;) = {,,, <Suppose that a sample of data is available from which either the sample mean, ¯, or the sample median, m, can be calculated.