Dependence Models Arising from the Lagrangian Probability Distributions

In this article, we propose a method based on the Lagrangian probability distributions for developing new dependence models. Specifically, a generalized Poisson–gamma dependence model is derived. The maximum likelihood estimation (MLE) technique is proposed for estimating the dependence model parameters. Application of the generalized Poisson–gamma dependence model is illustrated by using an operational risks dataset.     

Conditions of Slope-Rotatability for Third-Order Polynomial Regression Models

In experimental design for response surface analysis, it is sometimes of interest to estimate the difference of responses at two points. If differences at points close together are involved, the design that reliably estimates the slope of the response surface is important. In particular, Hader and Park (1978 Hader , R. J. , Park , S. H. ( 1978 ). Slope-rotatable central composite designs . Technometrics 20 : 413 – 417 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) suggested the concept of slope-rotatability and studied slope rotatable central composite designs. Until now, many response surface designs including central composite designs have been suggested for fitting second order response surface models. However, we often need to fit third-order polynomial regression models. In this article, we suggest extended central composite designs (ECCDs) to fit third-order models and find the necessary and sufficient conditions for slope-rotatability over all directions in the third-order polynomial models.     

Robust precision matrix estimation via weighted median regression with regularization

A precision matrix is an important parameter of interests because its elements describe useful association information among multiple variables, which has a wide variety of applications. For example, it is used for inferring gene regulation networks in genomic studies and stock association networks in financial studies. However, in many cases, the precision matrix needs to be robustly estimated due to the presence of outliers. We propose estimating a sparse scaled precision matrix via weighted median regression with regularization. Our weighted median regression approach is consistent under various distributional assumptions including multivariate t‐ or contaminated Gaussian distributions. This fact is illustrated with simulation studies and a real data analysis with monthly stock return data. The Canadian Journal of Statistics 46: 265–278; 2018 © 2018 Statistical Society of Canada     

Complete convergence for weighted sums of negatively dependent random variables

In this paper, we obtain a complete convergence result for weighted sums of negatively dependent random variables under mild conditions of weights. This result generalizes and improves the result of Zarei and Jabbari (Stat Papers doi:, 2009). Our result also extends the result of Taylor et al. (Stoch Anal Appl 20:643–656, 2002) on unweighted average to a weighted average.     

A Comparison of Spatiotemporal Surveillance Methods for Nonhomogeneous Change Size

Spatiotemporal surveillance, especially in detection of emerging outbreaks is of particular importance. When an outbreak spreads across some areas, the incidence rate at the center of the outbreak area might be expected to be much higher than the rate at its edge. However, to the best of our knowledge, all existing methods assume a uniformly increasing rate across the entire area of the outbreak. The purpose of this study is to compare the performance of the spatiotemporal surveillance methods such as multivariate cumulative sum (MCUSUM) or multivariate exponentially weighted moving average (MEWMA) when the changes in size are nonhomogeneous. Monte Carlo simulations were conducted to examine the properties of these spatiotemporal surveillance methods and compared them in terms of the detection speed and the identification rate under various scenarios. The results showed that when nonhomogeneous change sizes are involved, the MCUSUM method taking into account spatial nonhomogeneity of increase rates yields a better identification than the method ignoring such change size pattern although the detection speeds are similar. Further, a case study for the detection of male thyroid cancer data in New Mexico in the United States was performed to demonstrate the applicability of these methods.     

Simultaneous variable selection and outlier identification in linear regression using the mean-shift outlier model

We provide a method for simultaneous variable selection and outlier identification using the mean-shift outlier model. The procedure consists of two steps: the first step is to identify potential outliers, and the second step is to perform all possible subset regressions for the mean-shift outlier model containing the potential outliers identified in step 1. This procedure is helpful for model selection while simultaneously considering outlier identification, and can be used to identify multiple outliers. In addition, we can evaluate the impact on the regression model of simultaneous omission of variables and interesting observations. In an example, we provide detailed output from the R system, and compare the results with those using posterior model probabilities as proposed by Hoeting et al. [Comput. Stat. Data Anal. 22 (1996), pp. 252-270] for simultaneous variable selection and outlier identification.     

Toward an Understanding of the Influence of Cultural Background and Domain Experience on the Effects of Risk‐Pricing Formats on Risk Perception

Risk‐information framing can be a powerful tool for aiding the communication of risk and improving decision making. However, little work has investigated the extent that these framing effects depend on the characteristics of the perceiver. In our study, we examine whether the effects of different risk‐pricing formats on risky choices are the same for all individuals, no matter their domain experience or cultural background, or whether there are interactions between these factors. Survey 1 revealed that three risk‐pricing formats of the same choice problem resulted in the same individuals making different risky choices (preference reversal), suggesting that risk perception was distorted by the risk‐pricing format manipulation. In Survey 2, the effects of the risk‐pricing formats were shown to differ by the participants’ cultural background (Asian vs. European) and the extent of their domain experience. The fact that there were no differences between the cultural or domain experience groups in their overall tendency to select riskier (cf. safer) choices indicates that risk behavior differences between groups are often closely linked to perceptual, rather than simply attitudinal, cognitive processes. The results demonstrate the complex, interactive cognitive processes that are used to encode risk information, involving the framing of the information and the cultural background and previous experiences of the individual. We conclude that it is important to consider the characteristics of the individual (e.g., culture, domain experience, etc.) when manipulating risk‐information framing with the aim of improving risk communication.     

Women Reconciling Paid and Unpaid Work in a Confucian Welfare State: The Case of South Korea

The participation of married women in the labour market has been increasing since industrialization in the 1960s in Korea; in 1999 it overtook that of unmarried women. This raises the issue of how women reconcile paid and unpaid work and how state policy responds to this issue. In Korea, there have been numerous policy reforms designed to support working women in combining work and family life. For example, a parental leave scheme was introduced in 1995 and maternity benefits were also introduced in 2001. However, it is doubtful whether these policies can be effective in practice in Korea, where Confucian traditions in respect of women's roles remain strong. Confucian tradition has long influenced Korean society culturally and socially. Although Korean society today is not as Confucian as in the past, some traditions still remain strong, particularly with regard to the family: for example filial piety, seniority, the married woman's responsibility for her parents‐in‐law. This paper will argue that Confucian tradition makes for difficulties in Korean women's experiences of reconciling paid and unpaid work and also affects the formation of state policy. The paper explores the impact of the Confucian welfare regimes on Korean women's experience of reconciling paid and unpaid care work, and questions the gendered characteristics of the Confucian welfare state.