In this paper we concentrate on testing for multiple changes in the mean of a series of independent random variables. Suggested method applies a maximum type test statistic. Our primary focus is on an effective calculation of critical values for very large sample sizes comprising (tens of)...

<Para ID="Par1">We give sufficient conditions which the mutation rate must satisfy for the convergence of the genetic algorithm when that rate is allowed to change throughout iterations. The empirical performance of the algorithm with regards to changes in the mutation parameter is explored via test functions,...</para>

We derive a new algorithm for calculating an exact confidence interval for a parameter of location or scale family, based on a two-sided hypothesis test on the parameter of interest, using some pivotal quantities. We use this algorithm to calculate approximate confidence intervals for the...

Finding the “best-fitting” circle to describe a set of points in two dimensions is discussed in terms of maximum likelihood estimation. Several combinations of distributions are proposed to describe the stochastic nature of points in the plane, as the points are considered to have a common,...

Maximum likelihood estimation of the concentration parameter of von Mises–Fisher distributions involves inverting the ratio <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$R_\nu=I_{\nu +1} / I_\nu $$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <msub> <mi>R</mi> <mi mathvariant="italic">ν</mi> </msub> <mo>=</mo> <msub> <mi>I</mi> <mrow> <mi mathvariant="italic">ν</mi> <mo>+</mo> <mn>1</mn> </mrow> </msub> <mo stretchy="false">/</mo> <msub> <mi>I</mi> <mi mathvariant="italic">ν</mi> </msub> </mrow> </math> </EquationSource> </InlineEquation> of modified Bessel functions and computational methods are required to invert these functions using...</equationsource></equationsource></inlineequation>

An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...

The prediction of breeding values depends on the reliable estimation of variance components. This complex task leads to nonlinear minimization problems that have to be solved by numerical algorithms. In order to evaluate the reliability of these algorithms benchmark problems have to be...