Combined estimating function for random coefficient models with correlated errors

ABSTRACT

Estimating functionshave been shown to be convenient to study inference for non linear time series models. Recently, Thavaneswaran et al. (2012 Thavaneswaran, A., Liang, Y., Frank, J. (2012). Inference for random coefficient volatility models. Stat. Probab. Lett. 82(12):2086–2090.[Crossref], [Web of Science ®] , [Google Scholar]) used combined estimating functions to study inference for random coefficient autoregressive (RCA) models with generalized autoregressive heteroscedasticity errors. While most RCA modeling assumes that the random term and the error are independent, Chandra and Taniguchi (2001 Chandra, S.A., Taniguchi, M. (2001). Estimating functions for nonlinear time series models. Ann. Inst. Stat. Math 53(1):125–141.[Crossref], [Web of Science ®] , [Google Scholar]) studied inference for RCA models with correlated errors using linear estimating functions. In this paper, we derive the quadratic estimating functions for the joint estimation of the conditional mean, variance, and correlation parameters of the RCA models with correlated errors.     

A note on estimation and test for the rayleigh amplitude distribution

In an expository paper, Siddiqui (1962), presented and investigated the origin of the Rayleigh Power Distribution.He also discussed the problems of estimation and fitting the distribution to some numerical data. In this article we discuss two problems connected with the Rayleigh Amplitude Distribution (RAD). The first is an extension to the work done by Siddiqui on estimation, where the second is concerned with testing the equality of several Rayleigh Amplitude Distributions, and in this context we derive the asymptotic null distribution of the test criterion.     

Inverse Adaptive Cluster Sampling with Unequal Selection Probabilities: Case Studies on Crab Holes and Arsenic Pollution

Adaptive cluster sampling is an efficient method of estimating the parameters of rare and clustered populations. The method mimics how biologists would like to collect data in the field by targeting survey effort to localised areas where the rare population occurs. Another popular sampling design is inverse sampling. Inverse sampling was developed so as to be able to obtain a sample of rare events having a predetermined size. Ideally, in inverse sampling, the resultant sample set will be sufficiently large to ensure reliable estimation of population parameters. In an effort to combine the good properties of these two designs, adaptive cluster sampling and inverse sampling, we introduce inverse adaptive cluster sampling with unequal selection probabilities. We develop an unbiased estimator of the population total that is applicable to data obtained from such designs. We also develop numerical approximations to this estimator. The efficiency of the estimators that we introduce is investigated through simulation studies based on two real populations: crabs in Al Khor, Qatar and arsenic pollution in Kurdistan, Iran. The simulation results show that our estimators are efficient.     

The Jewish Issue in Islamic Radicalism: Historicity,Impact and Evolutions

This article focuses on the long‐term ideological vision of Jews and Israel in radical Islam. By examining, on the one hand, the animosity towards Judeo‐Israelis in the spawning and bolstering of Islamist, Salafist and Jihadist movements, and on the other hand, the sociological composition of Jihadist elites related to the Israeli‐Palestinian conflict, I show the centrality of the Judeophobic discourse in the world of radical Islam as well as the importance of Israel in its reinforcement. By trying to historicize this discourse, as well as political and strategic movements linked with the State of Israel, I also question the nature of the hostility towards Judaism, and more specifically the role of the Israeli issue in the development and evolution of the most radical and violent forms of Muslim identity over nearly a century.     

Antecedents and Consequences of Marital Satisfaction in an Emirati Sample: A Structural Equation Model Analysis

This study surveyed 1,000 married Emirati men and women to explore a model of marital satisfaction in relation to self-esteem, satisfaction with life, gender-role attitudes, and general health (physical and psychological). The Emirati Marital Satisfaction Scale (EMSS), State Self-Esteem Scale (SSES), Satisfaction With Life Scale (SWLS), the Arabic General Health Questionnaire, and the Sex-Role Egalitarianism Scale were used. Confirmatory factor analysis (CFA) on the EMSS indicated a moderate fit of the data to one factor structure. CFA on SSES and SWLS indicated an adequate fit of the data to the four-factor solution and one factor, respectively. The structural equation model for the EMSS showed that both general health and gender-role attitudes predict marital satisfaction and that marital satisfaction seems to predict the individual’s well-being as measured by life satisfaction and self-esteem. These results are discussed within the context of the United Arab Emirates culture and directions for future research are provided.     

Stopping rules for long-term clinical trials based on two consecutive rejections of the null hypothesis

A strategy for stopping long-term randomized clinical trials with time-to-event as a primary outcome measure has been considered using the criteria requiring multiple consecutive (or non consecutive) rejections at a specified α-level that controls against elevation of type I error. The procedure using two consecutive rejections is presented in this work along with the corresponding α-levels for the interim tests. The boundary cutoff values for these interim levels were determined based on an overall prespecified test size and were calculated using multidimensional integration and/or simulations. The reduction in the interim α-level values that is required to maintain the experiment-wise error rate is found to be modest. The power of the test is evaluated under various alternative accrual and hazard patterns. This procedure provides a more realistic stopping rule in large multi-center trials where it may be undesirable to terminate a trial unless a sustained effect has been demonstrated.     

Bayesian inference and prediction of the Pareto distribution based on ordered ranked set sampling

In this paper, order statistics from independent and non identically distributed random variables is used to obtain ordered ranked set sampling (ORSS). Bayesian inference of unknown parameters under a squared error loss function of the Pareto distribution is determined. We compute the minimum posterior expected loss (the posterior risk) of the derived estimates and compare them with those based on the corresponding simple random sample (SRS) to assess the efficiency of the obtained estimates. Two-sample Bayesian prediction for future observations is introduced by using SRS and ORSS for one- and m-cycle. A simulation study and real data are applied to show the proposed results.     

A coordinate descent algorithm for computing penalized smooth quantile regression

The computation of penalized quantile regression estimates is often computationally intensive in high dimensions. In this paper we propose a coordinate descent algorithm for computing the penalized smooth quantile regression (cdaSQR) with convex and nonconvex penalties. The cdaSQR approach is based on the approximation of the objective check function, which is not differentiable at zero, by a modified check function which is differentiable at zero. Then, using the maximization-minimization trick of the gcdnet algorithm (Yang and Zou in, J Comput Graph Stat 22(2):396–415, 2013), we update each coefficient simply and efficiently. In our implementation, we consider the convex penalties \(\ell _1+\ell _2\) and the nonconvex penalties SCAD (or MCP) \(+ \ell _2\). We establishe the convergence property of the csdSQR with \(\ell _1+\ell _2\) penalty. The numerical results show that our implementation is an order of magnitude faster than its competitors. Using simulations we compare the speed of our algorithm to its competitors. Finally, the performance of our algorithm is illustrated on three real data sets from diabetes, leukemia and Bardet–Bidel syndrome gene expression studies.     

Multiscale local polynomial decompositions using bandwidths as scales

The multiscale local polynomial transform, developped in this paper, combines the benefits from local polynomial smoothing with sparse multiscale decompositions. The contribution of the paper is twofold. First, it focusses on the bandwidths used throughout the transform. These bandwidths operate as user controlled scales in a multiscale analysis, which is explained to be of particular interest in the case of nonequispaced data. The paper presents both a likelihood based optimal bandwidth selection and a fast, heuristic approach. The second contribution of the paper is the combination of local polynomial smoothing with orthogonal prefilters, similar to Daubechies’ wavelet filters, but defined on irregularly spaced covariate values.     

A systematic review of research into the management of manufacturing capabilities

Abstract

Our study aims to explore the past and present knowledge related to the management of manufacturing capabilities and to assess the extent to which our knowledge of this field has developed. It places specific emphasis on the philosophical foundations of the field, while also providing a set of directions for future research. A systematic review is applied, covering 104 articles. The authors unfold a strong dominance of the positivist paradigm and call for a more balanced and informed approach in philosophical and, more specifically, methodological selection by scholars. In terms of the research content, a strong bias exists towards measuring the impact that certain manufacturing capabilities and various configurations of these may have on key performance indicators, such as cost. Our review warns on the dangers of following a dominant paradigmatic stance and on the limitations of researching a limited area of the complex and dynamic manufacturing capabilities arena.