The bahadur efficiency of paired versus joint ranking procedures for pa1rwtse multiple comparisons

The performance of paired versus joint ranking procedures for pairwise multiple comparisons is investigated using approxiirete Bahadur efficiency, When the populations to be compared are widely separated, or-when the. data arise from a shift model with an underlying unimodal density, the paired ranking procedure is found to be better for comparing two adjacent populations while the joint ranking procedure is more efficient for comparing the two most distant populations     

D‐optimal minimax fractional factorial designs

The D‐optimal minimax criterion is proposed to construct fractional factorial designs. The resulting designs are very efficient, and robust against misspecification of the effects in the linear model. The criterion was first proposed by Wilmut & Zhou (2011); their work is limited to two‐level factorial designs, however. In this paper we extend this criterion to designs with factors having any levels (including mixed levels) and explore several important properties of this criterion. Theoretical results are obtained for construction of fractional factorial designs in general. This minimax criterion is not only scale invariant, but also invariant under level permutations. Moreover, it can be applied to any run size. This is an advantage over some other existing criteria. The Canadian Journal of Statistics 41: 325–340; 2013 © 2013 Statistical Society of Canada     

Problems of Modeling Growth and Yield of Renewable Resources

Statistical Aspects of Quality Control. Cyrus DERMAN &; Sheldon M. ROSS, San Diego: Academic Press, 1997, xiii + 200 pp. $59.95 (H). Reviewed by Enrique Del Castillo

Handbook of Parametric and Nonparametric Statistical Procedures. David J. SHESKIN. Boca Raton: CRC Press, 1997, 719 pp. $69.95 (H). Reviewed by Karen KAFADAR

A Teacher's Review of the Chance Database. http://www.geom.umn.edu/locate/chance. Reviewed by Joan Garfield     

Resolution v.2 search designs

A fractional factorial design is called a resolution V.2 plan if it is capable of estimating all main effects and two-factor interaction effects, plus two three-factor interaction effects, In this paper, a necessary and sufficient condition for such a resolution V.2 plan is given, Furthermore, a new class of two-level resolution V.2 designs is proposed, We prove that the proposed design always satisfies such a necessary and sufficient condition, A comparison of run size between designs of resolutions VII and V.2 is made, It is shown that run size for design of resolution V.2 is significantly smaller.     

A central limit theorem for correlated variables with limited normal or gamma distributions

Abstract

Non-negative limited normal or gamma distributed random variables are commonly used to model physical phenomenon such as the concentration of compounds within gaseous clouds. This paper demonstrates that when a collection of random variables with limited normal or gamma distributions represents a stationary process for which the underlying variables have exponentially decreasing correlations, then a central limit theorem applies to the correlated random variables.     

On the MacMahon cube law for election results

This note was prompted by remarks of Stanton (1980) which suggest a procedure MacMahon may have used in arriving at the cube law for election results. We begin by briefly reviewing the law and the mystery surrounding its original motivation. We end by assessing Stanton's contribution to the solution of the mystery and pointing out alternative laws.