Instances of the Meijer G function may be used as representations for the probability density fun... more Instances of the Meijer G function may be used as representations for the probability density function (p.d.f.) and cumulative density function (c.d.f.) of several distributions. However, although the Meijer G function is a very handy representation for the p.d.f. and c.d.f. of these distributions, and nevertheless prominent progress has been made in its computation, this still remains very heavy, and time consuming, even with the newer versions of symbolic and extended precision softwares, so that the development of sharp and fast approximations is a desirable goal. In this paper it is shown how extremely sharp approximations for particular instances of the Meijer G function may be based on the probability density and cumulative distribution functions of the Generalized Near-Integer Gamma distribution.
In this paper we show first how the distribution of the logarithm of a random variable with a Bet... more In this paper we show first how the distribution of the logarithm of a random variable with a Beta distribution may be expressed either as a mixture of Gamma distributions or as a mixture of Generalized Integer Gamma (GIG) distributions and then how the exact distribution of the product of an odd number of independent Beta random variables whose first parameter evolves by 1/2 and whose second parameter is the half of an odd integer may be expressed as a mixture of GIG distributions. Some particularities of these mixtures are analysed. The results are then used to obtain the exact distribution of the logarithm of the Wilks Λ statistic to test the independence of two sets of variables, both with an odd number of variables, and the exact distribution of the logarithm of the generalized Wilks Λ statistic to test the independence of several sets of variables, in the case where two or three of them have an odd number of variables. A discussion of relative advantages and disadvantages of the use of the exact versus near-exact distributions is carried out.
Journal of Statistical Planning and Inference, 2007
In this paper a measure of proximity of distributions, when moments are known, is proposed. Based... more In this paper a measure of proximity of distributions, when moments are known, is proposed. Based on cases where the exact distribution is known, evidence is given that the proposed measure is accurate to evaluate the proximity of quantiles (exact vs. approximated). The measure may be applied to compare asymptotic and near-exact approximations to distributions, in situations where although being known the exact moments, the exact distribution is not known or the expression for its probability density function is not known or too complicated to handle. In this paper the measure is applied to compare newly proposed asymptotic and near-exact approximations to the distribution of the Wilks Lambda statistic when both groups of variables have an odd number of variables. This measure is also applied to the study of several cases of telescopic near-exact approximations to the exact distribution of the Wilks Lambda statistic based on mixtures of generalized near-integer gamma distributions.
In this paper, exact distribution of the product of independent beta random variables has been de... more In this paper, exact distribution of the product of independent beta random variables has been derived and its structural form is given together with recurrence relations for the coefficients of this representation. These recurrence relations yield a direct computational algorithm for computing the percentage points of many test criteria in multivariate statistical analysis.
In this paper, exact distribution of the product of independent beta random variables has been de... more In this paper, exact distribution of the product of independent beta random variables has been derived and its structural form is given together with recurrence relations for the coefficients of this representation. These recurrence relations yield a direct computational algorithm for computing the percentage points of many test criteria in multivariate statistical analysis.
In this paper we show first how the distribution of the logarithm of a random variable with a Bet... more In this paper we show first how the distribution of the logarithm of a random variable with a Beta distribution may be expressed either as a mixture of Gamma distributions or as a mixture of Generalized Integer Gamma (GIG) distributions and then how the exact distribution of the product of an odd number of independent Beta random variables whose first parameter evolves by 1/2 and whose second parameter is the half of an odd integer may be expressed as a mixture of GIG distributions. Some particularities of these mixtures are analysed. The results are then used to obtain the exact distribution of the logarithm of the Wilks Λ statistic to test the independence of two sets of variables, both with an odd number of variables, and the exact distribution of the logarithm of the generalized Wilks Λ statistic to test the independence of several sets of variables, in the case where two or three of them have an odd number of variables. A discussion of relative advantages and disadvantages of the use of the exact versus near-exact distributions is carried out.
Instances of the Meijer G function may be used as representations for the probability density fun... more Instances of the Meijer G function may be used as representations for the probability density function (p.d.f.) and cumulative density function (c.d.f.) of several distributions. However, although the Meijer G function is a very handy representation for the p.d.f. and c.d.f. of these distributions, and nevertheless prominent progress has been made in its computation, this still remains very heavy, and time consuming, even with the newer versions of symbolic and extended precision softwares, so that the development of sharp and fast approximations is a desirable goal. In this paper it is shown how extremely sharp approximations for particular instances of the Meijer G function may be based on the probability density and cumulative distribution functions of the Generalized Near-Integer Gamma distribution.
In this paper we show first how the distribution of the logarithm of a random variable with a Bet... more In this paper we show first how the distribution of the logarithm of a random variable with a Beta distribution may be expressed either as a mixture of Gamma distributions or as a mixture of Generalized Integer Gamma (GIG) distributions and then how the exact distribution of the product of an odd number of independent Beta random variables whose first parameter evolves by 1/2 and whose second parameter is the half of an odd integer may be expressed as a mixture of GIG distributions. Some particularities of these mixtures are analysed. The results are then used to obtain the exact distribution of the logarithm of the Wilks Λ statistic to test the independence of two sets of variables, both with an odd number of variables, and the exact distribution of the logarithm of the generalized Wilks Λ statistic to test the independence of several sets of variables, in the case where two or three of them have an odd number of variables. A discussion of relative advantages and disadvantages of the use of the exact versus near-exact distributions is carried out.
Journal of Statistical Planning and Inference, 2007
In this paper a measure of proximity of distributions, when moments are known, is proposed. Based... more In this paper a measure of proximity of distributions, when moments are known, is proposed. Based on cases where the exact distribution is known, evidence is given that the proposed measure is accurate to evaluate the proximity of quantiles (exact vs. approximated). The measure may be applied to compare asymptotic and near-exact approximations to distributions, in situations where although being known the exact moments, the exact distribution is not known or the expression for its probability density function is not known or too complicated to handle. In this paper the measure is applied to compare newly proposed asymptotic and near-exact approximations to the distribution of the Wilks Lambda statistic when both groups of variables have an odd number of variables. This measure is also applied to the study of several cases of telescopic near-exact approximations to the exact distribution of the Wilks Lambda statistic based on mixtures of generalized near-integer gamma distributions.
In this paper, exact distribution of the product of independent beta random variables has been de... more In this paper, exact distribution of the product of independent beta random variables has been derived and its structural form is given together with recurrence relations for the coefficients of this representation. These recurrence relations yield a direct computational algorithm for computing the percentage points of many test criteria in multivariate statistical analysis.
In this paper, exact distribution of the product of independent beta random variables has been de... more In this paper, exact distribution of the product of independent beta random variables has been derived and its structural form is given together with recurrence relations for the coefficients of this representation. These recurrence relations yield a direct computational algorithm for computing the percentage points of many test criteria in multivariate statistical analysis.
In this paper we show first how the distribution of the logarithm of a random variable with a Bet... more In this paper we show first how the distribution of the logarithm of a random variable with a Beta distribution may be expressed either as a mixture of Gamma distributions or as a mixture of Generalized Integer Gamma (GIG) distributions and then how the exact distribution of the product of an odd number of independent Beta random variables whose first parameter evolves by 1/2 and whose second parameter is the half of an odd integer may be expressed as a mixture of GIG distributions. Some particularities of these mixtures are analysed. The results are then used to obtain the exact distribution of the logarithm of the Wilks Λ statistic to test the independence of two sets of variables, both with an odd number of variables, and the exact distribution of the logarithm of the generalized Wilks Λ statistic to test the independence of several sets of variables, in the case where two or three of them have an odd number of variables. A discussion of relative advantages and disadvantages of the use of the exact versus near-exact distributions is carried out.
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Papers by Rui Alberto