Statistics Toolbox

nbinfit

Parameter estimates and confidence intervals for negative binomial data

Syntax

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

Description

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

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

[...] = nbinfit(...,options) specifies control parameters for the numerical optimization used to compute MLEs. Create this argument with the MATLAB optimset function. The default is optimset('Display','notify').

Note    The variance of a negative binomial distribution is greater than its mean. If the sample variance of the data x 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, optimset

nbincdf

nbininv