ASAS/IMLMacro for Computing Percentage Points of Pearson Distributions

Relative Increments of Pearson Distributions

This paper is a direct continuation of [6] whose results are applied to Pearson distributions, particularly to normal, gamma, beta of the rst kind, Pareto of the second kind, chi-square and other speci c distributions. Acta Mathematica Academiae Paedagogicae Ny regyh aziensis 15 (1999), 45{54 www.bgytf.hu/~amapn In this paper we investigate the hazard rate and relative increment functions of Pe...

Algorithms for Computing Limit distributions of Oscillating Systems with Finite Capacity

We address the batch arrival  systems with finite capacity under partial batch acceptance strategy where service times or rates oscillate between two forms according to the evolution of the number of customers in the system. Applying the theory of Markov regenerative processes and resorting to Markov chain embedding, we present a new algorithm for computing limit distributions of the number cus...

Computing percentage points of the largest among Student's t random variables

An approach is proposed for computing the percentile points of the maximum of k independent Student’s t random variables. A simple program in R (a freely downloadable statistical software) is presented and its performance compared with other known approaches. Similar programs are presented for computing the percentile points of the componentwise maximum of k-variate t and k-variate normal vecto...

Computing Closest Points for Segments

Computing Ideals of Points

The easiest geometric object in affine or projective space is a single rational point. It has no secrets, in particular its defining ideal, i.e. the set of all the polynomials which vanish at the point, is straightforward to describe. Namely, for an affine point with coordinates (a1, . . . , an), the corresponding ideal is p = (x1 − a1, . . . , xn − an); while for a projective point with coordi...