Testing non-oblique hypotheses

This paper considers a likelihood ratio test for testing hypotheses defined by non-oblique closed convex cones, satisfying the so called iteration projection property, in a set of k normal means. We obtain the critical values of the test using the Chi-Bar-Squared distribution. The obtuse cones are introduced as a particular class of cones which are non-oblique with every one of their faces. Examples with the simple tree order cone and the total order cone are given to illustrate the results.     

Two-stage chain sampling plans chsp-(0,2) and chsp-(l,2) - part 1

This article outlines the structure of a generalized family of two-stage chain sampling plans, extending the concept of two-stage chain sampling plans of Dodge and Stephens (1966) which is an extension of the original work of Dodge (1955). Expressions are derived for the OC curves for two-stage chain sampling plans with (c₁,c₂) = (0,2) and (1,2). In the original work of Dodge (1955) only acceptance numbers of 0,1 were used and in the extension work of Dodge and Stephens (1966) acceptance numbers of (c₁,c₂) = (0,1), (0,2), (1,2), (0,3), (1,3), (0,4) and (1,4) were used with selected sets of values of k₁ and k₂ (the number of lots considered for cumulation in the first and second stage respectively). In this paper the OC curves are derived more generally for any k₁ and k₂combination for two-stage chain sampling plans with (c₁,c₂) = (0,2) and (1,2) and comparisons are made with respect to sample sizes and discriminating power, with the corresponding single and double sampling plans.     

Construction of New Three-Level Response Surface Designs

Response surface methodology is widely used for developing, improving, and optimizing processes in various fields. In this article, we present a method for constructing three-level designs in order to explore and optimize response surfaces combining orthogonal arrays and covering arrays in a particular manner. The produced designs achieve the properties of rotatability, predictive performance and efficiency for the estimation of a second-order model.     

A Framework for Time Varying Parameter Regression Modeling

A framework for time varying parameter regression models is developed and employed in modeling and forecasting price expectations, using the Livingston data. Alternative model formulations, which include various choices for both the stochastic processes generating the varying parameters and the sets of explanatory variables, are examined and compared by using this framework. These models, some of which have appeared elsewhere and some of which are new, are estimated and used to assess the expectations formation process.     

The relationship between open innovation,entrepreneurship, and introduction of new business models in Korean and Indonesian information technology enterprises

This case study sought to identify the relationships that can exist between open innovation, entrepreneurship, and the introduction of new business models at the enterprise level. Eleven Korean enterprises and five Indonesian enterprises were chosen, to obtain minimum research generality. While the number of enterprises is not great, it provides enough samples to determine the concrete relationships among these factors. The article starts by pointing out the general relationship between entrepreneurship, open innovation, and the introduction of a new business model. It examines two different contexts: the difference between the Seoul and Daegu regional innovation systems, and the difference between the Indonesian and Korean national innovation systems.     

Multiple Time Series Modeling and Extended Sample Cross-Correlations

This article provides an expository account of the multivariate autoregressive moving average models and proposes an extended sample cross-correlation approach for practical model identification. An iterative model building procedure for applying these models to real data is discussed and demonstrated by analyzing the 5-series U.S. Hog Data.     

Older Drivers Retiring From the Road: An Application of the Selection,Optimization, and Compensation Model

Purpose: This study uses the selection, optimization, and compensation (SOC) model to compare older adults who have given up driving, those who still drive, and those who drive less to identify differences in the three groups. Design and Methods: This cross-sectional study of 281 older adults is part of the Naturally Occurring Retirement Community Demonstration Project. Study participants completed interviews that included questions on demographics, health and functioning, mental health, social support, and current levels of engagement in activities including current driving status. Results: Data suggest that driving retirement is a process and that a substantial number of people are in the transitional stage, where they are less functional than those who still drive and more similar to those who have retired from the road. Implications: Given the similarity of those who drive less to those who have given up driving, front-line professionals and policy makers must work together to ease the transition to driving retirement for those without adequate ability to effectively compensate for their inability to continue to drive safely.