The problem of fitting a folded normal distribution by maximum likelihood has been described as 'not straightforward', and alternatives such as EM proposed. We suggest here that it is in fact straightforward t...
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The problem of fitting a folded normal distribution by maximum likelihood has been described as 'not straightforward', and alternatives such as EM proposed. We suggest here that it is in fact straightforward to fit such a distribution by direct numerical maximization of the likelihood. We demonstrate this in an example. The relevant R code is included.
The analysis of data from accelerated life-test experiments via the method of maximum likelihood estimation must, for a Weibull log-linear model, be performed numerically. This paper promotes a particular log-likeliho...
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The analysis of data from accelerated life-test experiments via the method of maximum likelihood estimation must, for a Weibull log-linear model, be performed numerically. This paper promotes a particular log-likelihood as the basis for such inferences, and introduces notation and formulae to aid the implementation of various numerical methods. Two examples illustrate the performance of a widely-used maximization technique;these examples indicate that the performance of this technique compares favorably with that from commercially available software.
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