Lognormal negative log-likelihood

`nlogL = lognlike(params,data)`

[nlogL,avar] = lognlike(params,data)

[...] = lognlike(params,data,censoring)

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

`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.

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