nlogL = normlike (params, x) returns the negative log-likelihood for the normal distribution, evaluated at parameters params(1) = mean and params(2) = standard deviation, given x. nlogL is a scalar.

[nlogL, avar] = normlike (params, x) 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 (params, x, censor) accepts a boolean vector of the same size as x that is 1 for observations that are right-censored and 0 for observations that are observed exactly.

[…] = normlike (params, x, censor, freq) accepts a frequency vector of the same size as x. freq typically contains integer frequencies for the corresponding elements in x, but it may contain any non-integer non-negative values. Pass in [] for censor to use its default value.

Further information about the normal distribution can be found at https://en.wikipedia.org/wiki/Normal_distribution

See also: normcdf, norminv, normpdf, normrnd, normfit, normstat

Source Code: normlike