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. |
See Also
nbincdf, nbininv, nbinpdf, nbinrnd, nbinstat, mle, statset
Negative Binomial Distribution
 | nbincdf | | nbininv |  |
Includes the most popular MATLAB recorded presentations with Q&A sessions led by MATLAB experts.
Get the Interactive Kit
Store 
