# lognlike

Lognormal negative loglikelihood

## Syntax

## Description

`[`

also returns the inverse of the Fisher information matrix `nlogL`

,`aVar`

] = lognlike(___)`aVar`

, using
any of the input argument combinations in the previous syntaxes. If values in
`params`

are the maximum likelihood estimates (MLEs) of the
parameters, `aVar`

is an approximation to the asymptotic covariance
matrix.

## Examples

## Input Arguments

## Output Arguments

## Alternative Functionality

`lognlike`

is a function specific to lognormal distribution.
Statistics and Machine Learning Toolbox™ also offers the generic functions `mlecov`

, `fitdist`

, `negloglik`

, and `proflik`

and the **Distribution
Fitter** app, which support various probability distributions.

`mlecov`

returns the asymptotic covariance matrix of the MLEs of the parameters for a distribution specified by a custom probability density function. For example,`mlecov(params,x,'pdf',@lognpdf)`

returns the asymptotic covariance matrix of the MLEs for the lognormal distribution.Create a

`LognormalDistribution`

probability distribution object by fitting the distribution to data using the`fitdist`

function or the**Distribution Fitter**app. The object property`ParameterCovariance`

stores the covariance matrix of the parameter estimates. To obtain the negative loglikelihood of the parameter estimates and the profile of the likelihood function, pass the object to`negloglik`

and`proflik`

, respectively.

## References

[1] Evans, M., N. Hastings, and B.
Peacock. *Statistical Distributions*. 2nd ed. Hoboken, NJ: John Wiley
& Sons, Inc., 1993.

[2] Lawless, J. F.
*Statistical Models and Methods for Lifetime Data*. Hoboken, NJ:
Wiley-Interscience, 1982.

[3] Meeker, W. Q., and L. A. Escobar.
*Statistical Methods for Reliability Data*. Hoboken, NJ: John Wiley
& Sons, Inc., 1998.

## Extended Capabilities

## See Also

`lognfit`

| `lognpdf`

| `logncdf`

| `logninv`

| `lognstat`

| `lognrnd`

| `LognormalDistribution`

| `negloglik`

| `proflik`

| `mlecov`

| `mle`

### Topics

**Introduced before R2006a**