Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 63, No. 2 (2001), pp. 243-259 (17 pages) The analysis of a sample of curves can be done by self-modelling regression ...
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 ...
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 ...
The likelihood equation for a logistic regression model does not always have a finite solution. Sometimes there is a nonunique maximum on the boundary of the parameter space, at infinity. The ...
Mixed model analyses via restricted maximum likelihood, fitting the so-called animal model, have become standard methodology for the estimation of genetic variances. Models involving multiple genetic ...
In operational risk measurement, the estimation of severity distribution parameters is the main driver of capital estimates, yet this remains a nontrivial challenge for many reasons. Maximum ...
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