Brenton C. Peters

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This paper addresses the problem of obtaining numerically maximum-likelihood estimates of the parameters for a mixture of normal distributions. In recent literature, a certain successive-approximations procedure, based on the likelihood equations, was shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however,(More)
In this note, we give necessary and sufficient conditions for a maximum-likelihood estimate of a subset of the proportions in a mixture of specified distributions. From these conditions, we derive likelihood equations satisfied by the maximum-likelihood estimate and discuss a successive-approximations procedure suggested by these equations for numerically(More)
Scots pine (Pinus sylvestris L.) sapwood was treated with quat-silicone micro-emulsion (<40 nm), amino-silicone macro-emulsion (110 nm), alkyl-modified silicone macro-emulsion (740 nm) and solutions of inorganic water glass. Three treatment concentrations of 5, 15 and 30% (w/w) were used for the impregnation of the test specimens. Termite resistance was(More)
Fig. 2. space by Patrick-Fisher's algorithm (solid line) and E (dotted line). Bayes error estimates for SONAR data transformed to IO-dimensional high-dimensional data these results might be more in favor of E.) This is a result of the fact that each iteration of simplex requires that the samples be transformed to the low-dimensional space, and then the(More)
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