Optimal balanced block designs for correlated observations

The construction of universally optimal designs, if such exist, is difficult to obtain, especially when there are some nuisance effects or correlated errors. The hub correlation is a special correlation structure with applications to experiments in genetics, networks and other areas in industry and agriculture. There may be restrictions on the correlation values of the hub structure depending on the experiment. Optimality of block designs under hub correlation has been studied for the case of a constant correlation value. In this article, we consider the hub structure when one of the correlation values is different from the others, and the universally optimal block designs, binary or non-binary, are theoretically obtained. Also, we introduce an algorithm to construct the optimal designs. The Canadian Journal of Statistics 48: 596–604; 2020 © 2020 Statistical Society of Canada     

An Improvement of the Nonparametric Bootstrap Test for the Comparison of the Coefficient of Variations

In this article, we propose a new test for examining the equality of the coefficient of variation between two different populations. The proposed test is based on the nonparametric bootstrap method. It appears to yield several appreciable advantages over the current tests. The quick and easy implementation of the test can be considered as advantages of the proposed test. The test is examined by the Monte Carlo simulations, and also evaluated using various numerical studies.     

Small-sample properties of covariance-adjusted survivorship data tests for treatment effect

Monte Carlo methods are used to examine the small-sample properties of 11 test statistics that can be used for comparing several treatments with respect to their mortality experiences while adjusting for covariables. The test statistics are investigated from three distinct models: the parametric, semiparametric and rank analysis of covariance (Quade, 1967) models. Four tests (likelihood ratio, Wald, conditional and unconditional score tests) from each of the first two models and three tests (based on rank scores) from the last model are discussed. The empirical size and power of the tests are investigated under a proportional hazards model in three situations: (1) the baseline hazard is correctly assumed to be Exponential, (2) the baseline hazard is incorrectly assumed to be Exponential, and (3) a treatment-covariate interaction is omitted from the analysis.     

Weighted extensions of generalized cumulative residual entropy and their applications

Abstract

In this paper, we consider weighted extensions of generalized cumulative residual entropy and its dynamic(residual) version. Our results include linear transformations, stochastic ordering, bounds, aging class properties and some relationships with other reliability concepts. We also define the conditional weighted generalized cumulative residual entropy and discuss some properties of its. For these concepts, we obtain some characterization results under some assumptions. Finally, we provide an estimator of the new information measure using empirical approach. In addition, we study large sample properties of this estimator.     

Referee Recognition

In most instances referees are indicated at the end of each paper which they referee. The help of the following individuals who have refereed papers for this journal is hereby acknowledged. Individuals who refereed papers which were handled during the period covered by Issues 1 through 4 of this volume are included in this list. The Editors wish to express their thanks to all of these.     

A new three-parameter ageing distribution

We propose a new three-parameter ageing distribution called the Weibull-Poisson (WP) distribution, which generalizes the exponential-Poisson (EP) distribution introduced by Kus (2007). This new distribution has a more general form of failure rate (hazard rate) function. With appropriate choice of parameter values, it is able to model three ageing classes of life distributions including decreasing failure rate (DFR), increasing failure rate (IFR), and modified upside-down-bathtub (MUBT)-shaped failure rate. It thus provides an alternative to many existing life distributions. Various properties of this distribution are discussed and the estimation of the parameters is considered by the expectation maximization (EM) algorithm. Also, the asymptotic variance-covariance matrices of these estimates are obtained. Furthermore, some expressions for the Rènyi and Shannon entropies are given. Simulation studies are performed and experimental results are illustrated based on a real data set.     

The resampling of entropies with the application of biodiversity

This paper discusses the bootstrap test of entropies. Since the comparison of entropies is of prime interest in applied fields, finding an appropriate way to carry out such a comparison is of utmost importance. This paper presents how resampling should be performed to obtain an accurate p-value. Although the test using a pair-wise bootstrap confidence interval (CI) has already been dealt with in few works, here the bootstrap tests are studied because it may demand quite a different resampling algorithm compared with the CI. Moreover, the multiple test is studied. The proposed tests appear to yield several appreciable advantages. The easy implementation and the power of the proposed test can be considered as advantages. Here the entropy of the discrete variable is studied. The proposed tests are examined using Monte Carlo investigations and also evaluated using various distributions.     

Fiscal stringency and fiscal sustainability: Panel evidence from the American state and local governments

Most state (and local) governments in the U.S. operate under formal fiscal rules which limit their ability to run budget deficits and resort to debt financing. A priori, one would expect to find evidence in favor of an intertemporally balanced budget, or fiscal sustainability, for these states, especially those characterized by a relatively high degree of fiscal stringency. We test this hypothesis for a panel of 47 state–local government units (1961–2006) using four budget balance definitions and several subsamples defined based on regional classifications, or presence of certain balanced budget requirements (BBRs). Our results, obtained from panel estimation techniques that allow for general forms of serial and cross-sectional dependence, suggest that a sufficient condition for “strong” sustainability is consistently satisfied for the full sample and all subsamples in relation to balances that include special funds and/or federal grants. However, we find evidence consistent with the “weak” version of sustainability for the full sample and some regional subsamples (particularly Far West dominated by California) in at least one of the two balances that exclude these items. Finally, the BBRs seem to matter only in relation to the sustainability of the more narrowly defined balances. We discuss the implications of these findings for the role of fiscal rules and federal grant policies.     

Measures of information for maximum ranked set sampling with unequal samples

Biradar and Santosha (2014 Biradar, B. S., and C. D. Santosha. 2014. Estimation of the mean of the exponential distribution using maximum ranked set sampling with unequal samples. Open Journal of Statistics 4:641–49.[Crossref] , [Google Scholar]) proposed maximum ranked set sampling procedure with unequal samples (MRSSU) to estimate the mean of the exponential distribution. In this paper, we consider information measures of MRSSU in terms of Shannon entropy, Rényi entropy and Kullback-Leibler (KL) information. We also compare the uncertainty and information content of MRSSU with simple random sampling and ranked set sampling data. Finally, we develop some characterization results in terms of cumulative entropy and failure entropy of MRSSU.