Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...
Relatedness between individuals is central to ecological genetics. Multiple methods are available to quantify relatedness from molecular data, including method-of-moment and maximum-likelihood ...
An explicit procedure is given to obtain the exact maximum likelihood estimates of the parameters in a regression model with ARMA time series errors with possibly nonconsecutive data. The method is ...
Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 54, No. 4 (2005), pp. 721-737 (17 pages) The paper discusses the estimation of an unknown population size n. Suppose that ...
An algorithm for the computation of a maximum likelihood estimate of the offspring distribution in a Bienaymé-Galton-Watson branching process is presented. Although the offspring distribution in ...
Maximum likelihood estimation of the parameters of a statistical model involves maximizing the likelihood or, equivalently, the log likelihood with respect to the parameters. The parameter values at ...
In the process of loan pricing, stress testing, capital allocation, modeling of probability of default (PD) term structure and International Financial Reporting Standard 9 expected credit loss ...
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