Using adaptive weighted least squares to reduce the lengths of confidence intervals

The author proposes an adaptive method which produces confidence intervals that are often narrower than those obtained by the traditional procedures. The proposed methods use both a weighted least squares approach to reduce the length of the confidence interval and a permutation technique to insure that its coverage probability is near the nominal level. The author reports simulations comparing the adaptive intervals to the traditional ones for the difference between two population means, for the slope in a simple linear regression, and for the slope in a multiple linear regression having two correlated exogenous variables. He is led to recommend adaptive intervals for sample sizes superior to 40 when the error distribution is not known to be Gaussian.     

Predicting infectious disease outbreak risk via migratory waterfowl vectors

The spread of an emerging infectious disease is a major public health threat. Given the uncertainties associated with vector-borne diseases, in terms of vector dynamics and disease transmission, it is critical to develop statistical models that address how and when such an infectious disease could spread throughout a region such as the USA. This paper considers a spatio-temporal statistical model for how an infectious disease could be carried into the USA by migratory waterfowl vectors during their seasonal migration and, ultimately, the risk of transmission of such a disease to domestic fowl. Modeling spatio-temporal data of this type is inherently difficult given the uncertainty associated with observations, complexity of the dynamics, high dimensionality of the underlying process, and the presence of excessive zeros. In particular, the spatio-temporal dynamics of the waterfowl migration are developed by way of a two-tiered functional temporal and spatial dimension reduction procedure that captures spatial and seasonal trends, as well as regional dynamics. Furthermore, the model relates the migration to a population of poultry farms that are known to be susceptible to such diseases, and is one of the possible avenues toward transmission to domestic poultry and humans. The result is a predictive distribution of those counties containing poultry farms that are at the greatest risk of having the infectious disease infiltrate their flocks assuming that the migratory population was infected. The model naturally fits into the hierarchical Bayesian framework.     

A course in constructing effective displays of data for pharmaceutical research personnel

Interpreting data and communicating effectively through graphs and tables are requisite skills for statisticians and non‐statisticians in the pharmaceutical industry. However, the quality of visual displays of data in the medical and pharmaceutical literature and at scientific conferences is severely lacking. We describe an interactive, workshop‐driven, 2‐day short course that we constructed for pharmaceutical research personnel to learn these skills. The examples in the course and the workshop datasets source from our professional experiences, the scientific literature, and the mass media. During the course, the participants are exposed to and gain hands‐on experience with the principles of visual and graphical perception, design, and construction of both graphic and tabular displays of quantitative and qualitative information. After completing the course, with a critical eye, the participants are able to construct, revise, critique, and interpret graphic and tabular displays according to an extensive set of guidelines. Copyright © 2013 John Wiley & Sons, Ltd.     

Statistical analysis for Kumaraswamy’s distribution based on record data

In this paper we review some results that have been derived on record values for some well known probability density functions and based on m records from Kumaraswamy’s distribution we obtain estimators for the two parameters and the future sth record value. These estimates are derived using the maximum likelihood and Bayesian approaches. In the Bayesian approach, the two parameters are assumed to be random variables and estimators for the parameters and for the future sth record value are obtained, when we have observed m past record values, using the well known squared error loss (SEL) function and a linear exponential (LINEX) loss function. The findings are illustrated with actual and computer generated data.     

Non-negative estimation of variance components in heteroscedastic one-way random-effects ANOVA models

There is a considerable amount of literature dealing with inference about the parameters in a heteroscedastic one-way random-effects ANOVA model. In this paper, we primarily address the problem of improved quadratic estimation of the random-effect variance component. It turns out that such estimators with a smaller mean squared error compared with some standard unbiased quadratic estimators exist under quite general conditions. Improved estimators of the error variance components are also established.     

Book review

W.G.Cochran: Sampling Techniques, 3rd. Ed. John Wiley & Sons, New York-Santa Barbara-London-Sydney-Toronto 1977. 428 S., £ 12.50; $21.50.

H.Toutenburg: Vorhersage in linearen Modellen. Akademie-Verlag, Berlin 1975, VIII, 176b S., 3 Tab., 28,– M.

O.Kallenberg: Random Measure. Akademie-Verlag, Berlin 1975; Academic Press, London 1976. 104 pp., 28,– M.     

Book reviews

E. Kofler, G. Menges: Entscheidungen bei unvollständiger Information. Lecture Notes in Economics and Mathematical Systems 136. Springer-Verlag, Berlin-Heidelberg-NewYork 1976, 357 S., DM 31.

B. S. Everitt: The Analysis ot Contingency Tables. Chapman and Han, London 1977, 128 S., £ 3.75.

O. Barndorff-Nielsen: Information and Exponential Families in Statistical Theory. J. Wiley & Sons, Chichester-New York-Brisbane-Toronto 1978, 247 S., £ 13.50; $ 28.50.

W. Gilchrist: Statisticai Forecasting. J. Wiley & Sons, London-New York-Sydney-Toronto 1976, 321 S., £ 9.50; $ 19.00.

J. M. Chambers: Computational Methods for Data Analysis. J. Wiley & Sons, New York Chichester-Brisbane-Toronto 1977, 279 pp., £ 11.30.

A. Hughes, D. Grawoig: Statistics: A Foundation for Analysis. Addison-Wesley Publishing Company, Reading-Menlo-Park London-Don Mills 1971, 525 S., $ 11.50.

K.Krickeberg, H.Ziezold: Stochastiche Methoden. Springer Verlag, Berlin-Heidelberg-New York 1977, 201 S., 13 Abb., DM 28.

Ch. Schneeweiss: Inventory-Production Theory. A Linear Policy Approach. Lecture Notes in Economics and Mathematical Systems 151. Springer Verlag, Berlin-Heidelberg-NewYork 1977, 122 S., 13 Abb., 9 Tab., DM 18.

S. Dworatschek: Grundlagen der Datenverarbeltung, 6., völlig neu bearb. u. erw. Aufl., Walter de Gruyter, Berlin-New York 1977, 538 S., 200 Abb., 212 Üb.Aufg., 59 Fotos, DM 38.

H. E. Steinhagen, S. Fuchs:Objekterkennung. Einführung in die mathematischen Methoden der Zeichenerkennung. VEB Verlag Technik, Berlin 1976, 436 S., 165 Abb., 32 Tab., 49,–.M.

G. Tinhofer: Mathematik für Studlenanfänger, Carl Hanser Verlag, München 1977, 464 S., 191 Abb., DM 38.