They might be giants: a review of small presses and little magazines: an interview with Whitney Pastorek,Editor of Pindeldyboz

Abstract

This installment of “They Might Be Giants” highlights a small online/print zine from New York called Pindeldyboz. Described by its editor Whitney Pastorek as a lit mag, Pindeldyboz publishes new fiction every week or so at the Web site but then publishes longer fiction once a year in the annual print zine of the same name. While this may indicate a split personality on the part of the editor/publisher, the goals of both the print and online versions are the same: to publish good fiction.     

Hayter and Tsui's test with double sampling for the vector mean of multivariate normal population

Abstract

In this paper, we introduce a version of Hayter and Tsui's statistical test with double sampling for the vector mean of a population under multivariate normal assumption. A study showed that this new test was more or as efficient than the well-known Hotelling's T² with double sampling. Some nice features of Hayter and Tsui's test are its simplicity of implementation and its capability of identifying the errant variables when the null hypothesis is rejected. Taking that into consideration, a new control chart called HTDS is also introduced as a tool to monitor multivariate process vector mean when using double sampling.     

They might be giants: a review of small presses and little magazines: an interview with Whitney Pastorek, Editor of Pindeldyboz

This installment of “They Might Be Giants” highlights a small online/print zine from New York called Pindeldyboz. Described by its editor Whitney Pastorek as a lit mag, Pindeldyboz publishes new fiction every week or so at the Web site but then publishes longer fiction once a year in the annual print zine of the same name. While this may indicate a split personality on the part of the editor/publisher, the goals of both the print and online versions are the same: to publish good fiction.     

Estimation of a multivariate normal covariance matrix under a certain structure

We consider the estimation of Σ of the p-dimensional normal distribution N_p (0, Σ) when Σ?=?θ₀ I_p ?+?θ₁ aa′, where a is an unknown p-dimensional normalized vector and θ₀?>?0, θ₁?≥?0 are also unknown. First, we derive the restricted maximum likelihood (REML) estimator. Second, we propose a new estimator, which dominates the REML estimator with respect to Stein's loss function. Finally, we carry out Monte Carlo simulation to investigate the magnitude of the new estimator's superiority.     

Life in the Trenches of Print and Web Publishing: An Interview with Jessamyn West

Abstract

From Picas to Pixels has a peek into the life of librarian.net's founder and publisher, Jessamyn West. We talk about everything from library school to Colin Powell, from shell commands to the Internet community's recent infatuation with tagging (or what we catalogers like to call subject analysis). I tried to lead Jessamyn to admit that we need more catalogers in the mix on projects that are using tagging extensively, like Flickr.com and the Missouri Botanical Garden's new “tagswarming” project, but she did not take the bait.     

Reviews

Abstract

Jill M. Church reviews Exploring Discovery: The Front Door to Your Library's Licensed and Digitized Content; Scott Johnson reviews Now You're a Manager: Quick and Practical Strategies for New Mid-level Managers in Academic Libraries.     

Testing linear hypotheses in high-dimensional regressions

For a multivariate linear model, Wilk's likelihood ratio test (LRT) constitutes one of the cornerstone tools. However, the computation of its quantiles under the null or the alternative hypothesis requires complex analytic approximations, and more importantly, these distributional approximations are feasible only for moderate dimension of the dependent variable, say p≤20. On the other hand, assuming that the data dimension p as well as the number q of regression variables are fixed while the sample size n grows, several asymptotic approximations are proposed in the literature for Wilk's Λ including the widely used chi-square approximation. In this paper, we consider necessary modifications to Wilk's test in a high-dimensional context, specifically assuming a high data dimension p and a large sample size n. Based on recent random matrix theory, the correction we propose to Wilk's test is asymptotically Gaussian under the null hypothesis and simulations demonstrate that the corrected LRT has very satisfactory size and power, surely in the large p and large n context, but also for moderately large data dimensions such as p=30 or p=50. As a byproduct, we give a reason explaining why the standard chi-square approximation fails for high-dimensional data. We also introduce a new procedure for the classical multiple sample significance test in multivariate analysis of variance which is valid for high-dimensional data.     

Four Correlation Coefficients with a Third Blocking Variable: Their Efficacy,Relative Efficiency,and Test Statistics

Abstract

The efficacy and the asymptotic relative efficiency (ARE) of a weighted sum of Kendall's taus, a weighted sum of Spearman's rhos, a weighted sum of Pearson's r's, and a weighted sum of z-transformation of the Fisher–Yates correlation coefficients, in the presence of a blocking variable, are discussed. The method of selecting the weighting constants that maximize the efficacy of these four correlation coefficients is proposed. The estimate, test statistics and confidence interval of the four correlation coefficients with weights are also developed. To compare the small-sample properties of the four tests, a simulation study is performed. The theoretical and simulated results all prefer the weighted sum of the Pearson correlation coefficients with the optimal weights, as well as the weighted sum of z-transformation of the Fisher–Yates correlation coefficients with the optimal weights.     

Inferences Based on a Skipped Correlation Coefficient

The most popular method for trying to detect an association between two random variables is to test H ₀ ?:?ρ=0, the hypothesis that Pearson's correlation is equal to zero. It is well known, however, that Pearson's correlation is not robust, roughly meaning that small changes in any distribution, including any bivariate normal distribution as a special case, can alter its value. Moreover, the usual estimate of ρ, r, is sensitive to only a few outliers which can mask a true association. A simple alternative to testing H ₀ ?:?ρ =0 is to switch to a measure of association that guards against outliers among the marginal distributions such as Kendall's tau, Spearman's rho, a Winsorized correlation, or a so-called percentage bend correlation. But it is known that these methods fail to take into account the overall structure of the data. Many measures of association that do take into account the overall structure of the data have been proposed, but it seems that nothing is known about how they might be used to detect dependence. One such measure of association is selected, which is designed so that under bivariate normality, its estimator gives a reasonably accurate estimate of ρ. Then methods for testing the hypothesis of a zero correlation are studied.     

On Two Forms of Fisher's Measure of Information

ABSTRACT

Fisher's information number is the second moment of the “score function” where the derivative is with respect to x rather than Θ. It is Fisher's information for a location parameter, and also called shift-invariant Fisher information. In recent years, Fisher's information number has been frequently used in several places regardless of parameters of the distribution or of their nature. Is this number a nominal, standard, and typical measure of information? The Fisher information number is examined in light of the properties of classical statistical information theory. It has some properties analogous to those of Fisher's measure, but, in general, it does not have good properties if used as a measure of information when Θ is not a location parameter. Even in the case of location parameter, the regularity conditions must be satisfied. It does not possess the two fundamental properties of the mother information, namely the monotonicity and invariance under sufficient transformations. Thus the Fisher information number should not be used as a measure of information (except when Θ a location parameter). On the other hand, Fisher's information number, as a characteristic of a distribution f(x), has other interesting properties. As a byproduct of its superadditivity property a new coefficient of association is introduced.     

THE GENERALIZED SECANT HYPERBOLIC DISTRIBUTION AND ITS PROPERTIES

ABSTRACT

The properties of a family of distributions generalizing the secant hyperbolic are developed. This family consists of symmetric distributions, with kurtosis ranging from 1.8 to infinity, and includes the logistic as a special case, the uniform as a limiting case, and closely approximates the normal and Student's t-distributions with corresponding kurtosis. A significant difference between this family and Student's t is that for any member of the generalized secant hyperbolic family, all moments are finite. Further, technical difficulties associated with evaluating moments of Student's t (especially for fractional degrees of freedom) are not present with this family. The properties of the maximum likelihood and modified maximum likelihood estimates of the location and scale parameters for complete samples are considered. Examples illustrate the methods developed in this work.     

A new revised version of McNemar's test for paired binary data

By considering separately B and C, the frequencies of individuals who consistently gave positive or negative answers in before and after responses, a new revised version of McNemar's test is derived. It improves upon Lu's revised formula, which considers B and C together. When both B and C are 0, the new revised version produces the same results as McNemar's test. When one of B and C is 0, the new revised test produces the same results as Lu's version. Compared to Lu's version, the new revised test is a more complete revision of McNemar's test.     

An Interview with Ben Brown,Co-founder of So New Media and Publisher of Words! Words! Words!

Abstract

With this installment of “They Might Be Giants,” Michael Brown talks with Ben Brown (no relation) about publishing books (ten so far!) and magazines (issue 3 of Words! Words! Words! is about to be released), while at the same time working nine-to-five at a really boring tech job. It's a do-it-yourselfer's dream come true. Serials Review 2002; 28:344–348.     

Robust methods of estimation of regression coefficients 1

Recently, cumulative residual entropy (CRE) has been found to be a new measure of information that parallels Shannon's entropy (see Rao et al. [Cumulative residual entropy: A new measure of information, IEEE Trans. Inform. Theory. 50(6) (2004), pp. 1220–1228] and Asadi and Zohrevand [On the dynamic cumulative residual entropy, J. Stat. Plann. Inference 137 (2007), pp. 1931–1941]). Motivated by this finding, in this paper, we introduce a generalized measure of it, namely cumulative residual Renyi's entropy, and study its properties. We also examine it in relation to some applied problems such as weighted and equilibrium models. Finally, we extend this measure into the bivariate set-up and prove certain characterizing relationships to identify different bivariate lifetime models.     

Ohio Little Magazines

Abstract

The company now known as DC began as National Periodicals, publishing anthology series such as Adventure Comics, More Fun Comics, and Detective Comics. Superman, the first true “super-hero,” appeared on the scene in a brief story in Action Comics no. 1 (June, 1938). Batman appeared not long after, in the pages of Detective Comics no. 27 (May 1939)|3-and the world was never the same. In the late 1940s, National absorbed its competitor Ail-American Comics (which published such series as Green Lantern, Aquaman, and Green Arrow) and changed the company's name to Detective Comics, “DC” for short. The merger made DC the largest comic book company until the 1950s, when interest in the medium dried up, and Dell, who at that time published Walt Disney's comic books, took over the top spot.     

Selecting the Optimal Transformation of a Continuous Covariate in Cox's Regression: Implications for Hypothesis Testing

ABSTRACT

Background: Many exposures in epidemiological studies have nonlinear effects and the problem is to choose an appropriate functional relationship between such exposures and the outcome. One common approach is to investigate several parametric transformations of the covariate of interest, and to select a posteriori the function that fits the data the best. However, such approach may result in an inflated Type I error. Methods: Through a simulation study, we generated data from Cox's models with different transformations of a single continuous covariate. We investigated the Type I error rate and the power of the likelihood ratio test (LRT) corresponding to three different procedures that considered the same set of parametric dose-response functions. The first unconditional approach did not involve any model selection, while the second conditional approach was based on a posteriori selection of the parametric function. The proposed third approach was similar to the second except that it used a corrected critical value for the LRT to ensure a correct Type I error. Results: The Type I error rate of the second approach was two times higher than the nominal size. For simple monotone dose-response, the corrected test had similar power as the unconditional approach, while for non monotone, dose-response, it had a higher power. A real-life application that focused on the effect of body mass index on the risk of coronary heart disease death, illustrated the advantage of the proposed approach. Conclusion: Our results confirm that a posteriori selecting the functional form of the dose-response induces a Type I error inflation. The corrected procedure, which can be applied in a wide range of situations, may provide a good trade-off between Type I error and power.     

Transformations for Testing the Fit of the Inverse-Gaussian Distribution

Abstract

Use of the MVUE for the inverse-Gaussian distribution has been recently proposed by Nguyen and Dinh [Nguyen, T. T., Dinh, K. T. (2003). Exact EDF goodnes-of-fit tests for inverse Gaussian distributions. Comm. Statist. (Simulation and Computation) 32(2):505–516] where a sequential application based on Rosenblatt's transformation [Rosenblatt, M. (1952). Remarks on a multivariate transformation. Ann. Math. Statist. 23:470–472] led the authors to solve the composite goodness-of-fit problem by solving the surrogate simple goodness-of-fit problem, of testing uniformity of the independent transformed variables. In this note, we observe first that the proposal is not new since it was proposed in a rather general setting in O'Reilly and Quesenberry [O'Reilly, F., Quesenberry, C. P. (1973). The conditional probability integral transformation and applications to obtain composite chi-square goodness-of-fit tests. Ann. Statist. I:74–83]. It is shown on the other hand that the results in the paper of Nguyen and Dinh (2003) are incorrect in their Sec. 4, specially the Monte Carlo figures reported. Power simulations are provided here comparing these corrected results with two previously reported goodness-of-fit tests for the inverse-Gaussian; the modified Kolmogorov–Smirnov test in Edgeman et al. [Edgeman, R. L., Scott, R. C., Pavur, R. J. (1988). A modified Kolmogorov-Smirnov test for inverse Gaussian distribution with unknown parameters. Comm. Statist. 17(B): 1203–1212] and the A ² based method in O'Reilly and Rueda [O'Reilly, F., Rueda, R. (1992). Goodness of fit for the inverse Gaussian distribution. T Can. J. Statist. 20(4):387–397]. The results show clearly that there is a large loss of power in the method explored in Nguyen and Dinh (2003) due to an implicit exogenous randomization.     

Electronic journals and the paradigm shift: 1995 Spring forum of the Canadian Serials Industry Systems Advisory Committee

Abstract

Since 2006, Research Online, the University of Wollongong's open access institutional repository has utilised Bepress' Digital Commons software to make available published research outputs and digital theses. This article discusses the outcomes of recent academic demand for its use as a publishing tool of university journals and conference proceedings. The Journal of University Teaching and Learning Practice is provided as an example. Digital Commons includes the editorial management software, EdiKit, which assists in managing submissions, editorial functions, and peer review. Also considered are changes to scholarly communication patterns arising out of the new open access, electronic only, publication regimes.     

Reviews and Notices

Abstract

Statistics in Hungary: Geschichte und Organization der amtlichen Statistik in Ungarn. By Gustav Bokor. Pp. v, 291. Budapesth. Pester Buchdruckerei Active Gesellschaft, 1896.

Bertillon's Treatise: Cours élementaire de statistique conforme au programme arrêtépar le Gonseil Supérieur de Statistique pour l'examen d'admission dans diverses administrations publiques. By Dr. Jacques Bertillon, Chef des Travaux Statistiques of Paris, France. Three parts. Pp. 599. Paris, 1895.

Muhleman's Monetary System: Monetary Systems of the World. By Maurice L. Muhleman. Revised edition. New York, 1897. Pp. 239.

Notes: Financial Reform Almanac for 1897. London. Pp. 316.

Notes: Eighth Annual Report by the Chief Labor Correspondent on Trade Unions, 1894–95. London, 1896. Pp. xxix, 515.

Notes: Third Annual Report of the Labour Department of the Board of Trade, 1895–96, with Abstract of Labour Statistics. London, 1896. Pp. xxviii, 200.

Report of the Secretary of the American Statistical Association. Reviewed by Davis R. Dewey.