The Vanishing 2×2 Table: Linking the Hypergeometric,Binomial and Poisson

A simple procedure for establishing minimum sample size in X ² goodness-of-fit tests is presented. Samples of this size will automatically satisfy Yarnold's criterion.     

The Yule–Walker equations as a weighted least-squares problem and the association with tapering

ABSTRACT

A common method for estimating the time-domain parameters of an autoregressive process is to use the Yule–Walker equations. Tapering has been shown intuitively and proven theoretically to reduce the bias of the periodogram in the frequency domain, but the intuition for the similar bias reduction in the time-domain estimates has been lacking. We provide insightful reasoning for why tapering reduces the bias in the Yule–Walker estimates by showing them to be equivalent to a weighted least-squares problem. This leads to the derivation of an optimal taper which behaves similarly to commonly used tapers.     

The exponentiated exponential–geometric distribution: a distribution with decreasing,increasing and unimodal failure rate

In this paper, we proposed a new family of distributions namely exponentiated exponential–geometric (E2G) distribution. The E2G distribution is a straightforwardly generalization of the exponential–geometric (EG) distribution proposed by Adamidis and Loukas [A lifetime distribution with decreasing failure rate, Statist. Probab. Lett. 39 (1998), pp. 35–42], which accommodates increasing, decreasing and unimodal hazard functions. It arises on a latent competing risk scenarios, where the lifetime associated with a particular risk is not observable but only the minimum lifetime value among all risks. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulas for its survival and hazard functions, moments, rth moment of the ith order statistic, mean residual lifetime and modal value. Maximum-likelihood inference is implemented straightforwardly. From a mis-specification simulation study performed in order to assess the extent of the mis-specification errors when testing the EG distribution against the E2G, and we observed that it is usually possible to discriminate between both distributions even for moderate samples with presence of censoring. The practical importance of the new distribution was demonstrated in three applications where we compare the E2G distribution with several lifetime distributions.     

The Likelihood Ratio Test with the Box–Cox Transformation for the Normal Mixture Problem: Power and Sample Size Study

Abstract

Through simulation and regression, we study the alternative distribution of the likelihood ratio test in which the null hypothesis postulates that the data are from a normal distribution after a restricted Box–Cox transformation and the alternative hypothesis postulates that they are from a mixture of two normals after a restricted (possibly different) Box–Cox transformation. The number of observations in the sample is called N. The standardized distance between components (after transformation) is D = (μ₂ ? μ₁)/σ, where μ₁ and μ₂ are the component means and σ² is their common variance. One component contains the fraction π of observed, and the other 1 ? π. The simulation results demonstrate a dependence of power on the mixing proportion, with power decreasing as the mixing proportion differs from 0.5. The alternative distribution appears to be a non-central chi-squared with approximately 2.48 + 10N ^?0.75 degrees of freedom and non-centrality parameter 0.174N(D ? 1.4)² × [π(1 ? π)]. At least 900 observations are needed to have power 95% for a 5% test when D = 2. For fixed values of D, power, and significance level, substantially more observations are necessary when π ≥ 0.90 or π ≤ 0.10. We give the estimated powers for the alternatives studied and a table of sample sizes needed for 50%, 80%, 90%, and 95% power.     

The SLA DBIO 100 Poll: 100 Journals Voted by SLA’s BioMedical and Life Sciences Division as the Most Influential over the Last 100 Years

An expert opinion poll of the members of the BioMedical and Life Sciences Division (DBIO) of the Special Libraries Association (SLA), conducted on the occasion of the SLA's Centennial (Washington, DC, June 14–17, 2009), identified 100 journals across three major categories (Clinical Medicine and Allied Health Sciences, Journals Primarily Reporting Molecular and Cellular Biology, and Journals of Natural History) as the most influential over the last 100 years. The Top Ten, containing winners from all three of these groups, were also named, as were a “Journal” and a “Publisher” of the Centennial.”     

The SLA DBIO 100 Poll: 100 Journals Voted by SLA’s BioMedical and Life Sciences Division as the Most Influential over the Last 100 Years

Abstract

An expert opinion poll of the members of the BioMedical and Life Sciences Division (DBIO) of the Special Libraries Association (SLA), conducted on the occasion of the SLA's Centennial (Washington, DC, June 14–17, 2009), identified 100 journals across three major categories (Clinical Medicine and Allied Health Sciences, Journals Primarily Reporting Molecular and Cellular Biology, and Journals of Natural History) as the most influential over the last 100 years. The Top Ten, containing winners from all three of these groups, were also named, as were a “Journal” and a “Publisher” of the Centennial.”