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# lognlike

Lognormal negative log-likelihood

## Syntax

nlogL = lognlike(params,data)
[nlogL,avar] = lognlike(params,data)
[...] = lognlike(params,data,censoring)
[...] = lognlike(params,data,censoring,freq)

## Description

nlogL = lognlike(params,data) returns the negative log-likelihood of data for the lognormal distribution with parameters params. params(1) is the mean of the associated normal distribution, mu, and params(2) is the standard deviation of the associated normal distribution, sigma. The values of mu and sigma are scalars, and the output nlogL is a scalar.

[nlogL,avar] = lognlike(params,data) returns the inverse of Fisher's information matrix. If the input parameter value in params is the maximum likelihood estimate, avar is its asymptotic variance. avar is based on the observed Fisher's information, not the expected information.

[...] = lognlike(params,data,censoring) accepts a Boolean vector, censoring, of the same size as data, which is 1 for observations that are right-censored and 0 for observations that are observed exactly.

[...] = lognlike(params,data,censoring,freq) accepts a frequency vector, freq, of the same size as data. The vector freq typically contains integer frequencies for the corresponding elements in data, but can contain any nonnegative values. Pass in [] for censoring to use its default value.

## See Also

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