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distributions/

ln_like.pro

This function calculates the log-likelihood of the data, under a lognormal model. This distribution is given by f(x) = C * 1 / x * exp(-(ln(x) - mu)^2 / sigma^2) C = sqrt(2) / (sigma sqrt(pi)) / erfc( (ln(xmin) - mu) / sqrt(2 sigma) ) C simplifies to 1 / sqrt(2 pi sigma^2) if xmin = 0

To maximize speed, the function does not check for values of data < xmin. However, the output is useless when any data are < xmin.

toplognormal_MLE

result = lognormal_MLE(p, dp, data=data, xmin=xmin, _extra=_extra)

The maximum likelihood estimator for a set of data assuming a lognormal distribution. Partial derivatives provided.

Return value

MLE = -2 ln(product(p))

Parameters

p
dp

Keywords

data
xmin
_extra

Author information

History:

js: May 2009 - creation

File attributes

Modifcation date: Mon Mar 22 16:17:13 2010
Lines: 122