Normal negative log-likelihood


nlogL = normlike(params,data)
[nlogL,AVAR] = normlike(params,data)
[...] = normlike(param,data,censoring)
[...] = normlike(param,data,censoring,freq)


nlogL = normlike(params,data) returns the negative of the normal log-likelihood function. params(1) is the mean, mu, and params(2) is the standard deviation, sigma.

[nlogL,AVAR] = normlike(params,data) also returns the inverse of Fisher's information matrix, AVAR. If the input parameter values in params are the maximum likelihood estimates, the diagonal elements of AVAR are their asymptotic variances. AVAR is based on the observed Fisher's information, not the expected information.

[...] = normlike(param,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.

[...] = normlike(param,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.

normlike is a utility function for maximum likelihood estimation.

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