nbinfit

Negative binomial parameter estimates

Syntax

parmhat = nbinfit(data)
[parmhat,parmci] = nbinfit(data,alpha)
[...] = nbinfit(data,alpha,options)


Description

parmhat = nbinfit(data) returns the maximum likelihood estimates (MLEs) of the parameters of the negative binomial distribution given the data in the vector data.

[parmhat,parmci] = nbinfit(data,alpha) returns MLEs and 100(1-alpha) percent confidence intervals. By default, alpha = 0.05, which corresponds to 95% confidence intervals.

[...] = nbinfit(data,alpha,options) accepts a structure, options, that specifies control parameters for the iterative algorithm the function uses to compute maximum likelihood estimates. The negative binomial fit function accepts an options structure which you can create using the function statset. Enter statset('nbinfit') to see the names and default values of the parameters that nbinfit accepts in the options structure. See the reference page for statset for more information about these options.

Note

The variance of a negative binomial distribution is greater than its mean. If the sample variance of the data in data is less than its sample mean, nbinfit cannot compute MLEs. You should use the poissfit function instead.

Extended Capabilities

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Version History

Introduced before R2006a