Parammle: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
Maximum likelihood parameter estimates. | Maximum likelihood parameter estimates. | ||
===Synopsis=== | ===Synopsis=== | ||
:params = parammle(x,distname) | :params = parammle(x,distname) | ||
===Description=== | ===Description=== | ||
Use parammle to obtain the best fit parameter estimates for a supported distribution. | Use parammle to obtain the best fit parameter estimates for a supported distribution. | ||
'''Note''': Some distributions (beta, Cauchy, gamma, Gumbel, and Weibull) will take longer to find the maximum likelihood estimates as the estimators are not analytically known. They are solved for by optimizing the likelihood. | '''Note''': Some distributions (beta, Cauchy, gamma, Gumbel, and Weibull) will take longer to find the maximum likelihood estimates as the estimators are not analytically known. They are solved for by optimizing the likelihood. | ||
* x = matrix (column vector) in which the sample data is stored. | ====Inputs==== | ||
* distname = string, optional distribution name to assume as the parent distribution for the sample. Default value is 'normal'. | |||
* '''x''' = matrix (column vector) in which the sample data is stored. | |||
* '''distname''' = string, optional distribution name to assume as the parent distribution for the sample. Default value is 'normal'. | |||
====Outputs==== | |||
The return value is a structure with up to 3 fields depending on the distribution (distname). | The return value is a structure with up to 3 fields depending on the distribution (distname). | ||
* a = first paramter. | |||
* b = second parameter (if necessary). | * '''a''' = first paramter. | ||
* c = third parameter (if necessary). | |||
* '''b''' = second parameter (if necessary). | |||
* '''c''' = third parameter (if necessary). | |||
===Examples=== | ===Examples=== | ||
params = parammle(x,'exponential') | params = parammle(x,'exponential') | ||
===See Also=== | ===See Also=== | ||
[[chitest]] | [[chitest]] | ||
Latest revision as of 16:34, 3 September 2008
Purpose
Maximum likelihood parameter estimates.
Synopsis
- params = parammle(x,distname)
Description
Use parammle to obtain the best fit parameter estimates for a supported distribution.
Note: Some distributions (beta, Cauchy, gamma, Gumbel, and Weibull) will take longer to find the maximum likelihood estimates as the estimators are not analytically known. They are solved for by optimizing the likelihood.
Inputs
- x = matrix (column vector) in which the sample data is stored.
- distname = string, optional distribution name to assume as the parent distribution for the sample. Default value is 'normal'.
Outputs
The return value is a structure with up to 3 fields depending on the distribution (distname).
- a = first paramter.
- b = second parameter (if necessary).
- c = third parameter (if necessary).
Examples
params = parammle(x,'exponential')