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 ...
Linear ARCH (LARCH) processes were introduced by Robinson [J. Econometrics 47 (1991) 67-84] to model long-range dependence in volatility and leverage. Basic theoretical properties of LARCH processes ...
In this paper we consider maximum likelihood estimation of the rate constant for stochastic rth-Order reactions based on observation of the level of the system at time t > 0. Conditions are found for ...
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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