A semiparametric approach for modelling multivariate nonlinear time series

In this article, a semiparametric time‐varying nonlinear vector autoregressive (NVAR) model is proposed to model nonlinear vector time series data. We consider a combination of parametric and nonparametric estimation approaches to estimate the NVAR function for both independent and dependent errors. We use the multivariate Taylor series expansion of the link function up to the second order which has a parametric framework as a representation of the nonlinear vector regression function. After the unknown parameters are estimated by the maximum likelihood estimation procedure, the obtained NVAR function is adjusted by a nonparametric diagonal matrix, where the proposed adjusted matrix is estimated by the nonparametric kernel estimator. The asymptotic consistency properties of the proposed estimators are established. Simulation studies are conducted to evaluate the performance of the proposed semiparametric method. A real data example on short‐run interest rates and long‐run interest rates of United States Treasury securities is analyzed to demonstrate the application of the proposed approach. The Canadian Journal of Statistics 47: 668–687; 2019 © 2019 Statistical Society of Canada     

A new aging concept derived from the increasing convex ordering

In this paper, a comparison between the life distribution of a new unit with that of a used unit in the increasing convex order is made leading to a new class of life distributions which we call “new better than used in convex ordering of second order”. This class includes as subclasses the NBU and the NBUC and is a subclass of the NBUCA class. Preservation properties under convolution, random maxima, mixing and formation of coherent structures are established. Stochastic comparisons of the excess lifetime when the inter-arrival times belong to the NBUC(2) class are developed. Some applications of Poisson shock models and a test of exponentiality against NBUC(2) alternative are presented.     

The effect of small sample on optimal designs for logistic regression models

Asymptotic methods are commonly used in statistical inference for unknown parameters in binary data models. These methods are based on large sample theory, a condition which may be in conflict with small sample size and hence leads to poor results in the optimal designs theory. In this paper, we apply the second order expansions of the maximum likelihood estimator and derive a matrix formula for the mean square error (MSE) to obtain more precise optimal designs based on the MSE. Numerical results indicate the new optimal designs are more efficient than the optimal designs based on the information matrix.     

Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective

Statistics and Computing - We formulate probabilistic numerical approximations to solutions of ordinary differential equations (ODEs) as problems in Gaussian process (GP) regression with nonlinear...     

A reflected feature space for CART

We present an algorithm for learning oblique decision trees, called HHCART(G). Our decision tree combines learning concepts from two classification trees, HHCART and Geometric Decision Tree (GDT). HHCART(G) is a simplified HHCART algorithm that uses linear structure in the training examples, captured by a modified GDT angle bisector, to define splitting directions. At each node, we reflect the training examples with respect to the modified angle bisector to align this linear structure with the coordinate axes. Searching axis parallel splits in this reflected feature space provides an efficient and effective way of finding oblique splits in the original feature space. Our method is much simpler than HHCART because it only considers one reflected feature space for node splitting. HHCART considers multiple reflected feature spaces for node splitting making it more computationally intensive to build. Experimental results show that HHCART(G) is an effective classifier, producing compact trees with similar or better results than several other decision trees, including GDT and HHCART trees.     

Transnational queer sociological analysis of sexual identity and civic‐political activism in Hong Kong,Taiwan and mainland China

The sociology of homosexuality lacks engagement with queer theory and postcolonialism and focuses primarily on the global metropoles, thus failing to provide a plausible account of non‐Western non‐normative sexual identities. This research adopts the author’s newly proposed transnational queer sociology to address these deficiencies. First, it critiques the Western model of sexual identity predominantly employed to elucidate non‐Western, non‐normative sexualities. It does so by examining not only the queer flows between West and non‐West but also those among and within non‐Western contexts to produce translocally shared and mutually referenced experiences. Second, the proposed approach combines sociology with queer theory by emphasizing the significant role of material, as well as discursive, analyses in shaping queer identities, desires and practices. This article employs the approach to examine young gay male identities, as revealed in 90 in‐depth interviews conducted in Hong Kong (n = 30), Taiwan (Taipei, n = 30) and mainland China (Shanghai, n = 30) between 2017 and 2019. More specifically, it highlights the interplay between the state and identity by investigating the intersection and intertwining effects of these young men’s sexual and cultural/national identities, revealing three different forms of civic‐political activism. The article both demonstrates the way in which sexuality and the state are mutually constituted and provides nuanced analysis of the heterogeneity of contemporary homosexualities in Hong Kong, Taiwan and mainland China. In applying a new sociological approach to understanding sexuality, this research joins the growing body of scholarship within sociology that is decentring the Western formation of universal knowledge.     

White Ethnic Diversity in Small Town Iowa: A Multilevel Analysis of Community Attachment

Community attachment is the feeling of being connected to community life. Within the community attachment literature, two classic approaches frame scholars’ understanding of this important dimension of community life: the linear development and systemic models. Our empirical models emphasize different factors for community attachment, including population size, density, and heterogeneity for the linear development model and age, length of residence, and social status for the systemic model. Surprisingly, heterogeneity has been omitted from analyses of the linear development model throughout the literature since its introduction, a shortcoming our study addresses. Though heterogeneity can be conceptualized in a number of ways, a large—and growing—body of literature focuses on the effects of race and ethnicity for communities. Here, we focus on a particular type of ethnic heterogeneity—European ancestry—and reincorporate this essential dimension of communities back into the linear development model of community attachment. Using data from the 2004 wave of the Iowa Community Survey and multilevel modeling techniques, we explore how white ethnic diversity matters for community life. We conclude with a discussion of the implications of our study, including potential avenues for future research focusing on other ethnicities that are often subsumed under broader racial and panethnic labels.     

Trajectories of Limitations with Activities of Daily Living Among Older Adults of Mexican Descent: The Role of Widowhood

Using seven waves of data from the Hispanic Established Population for the Epidemiologic Study of the Elderly (1993–2011), this study applies multiphase growth models to examine changes in limitations with activities of daily living (ADL) across widowhood experience among 385 older adults of Mexican descent. This study also investigates the implications of demographic characteristics, health, socioeconomic status, living arrangements, and social involvement. ADL limitations increased pre-widowhood, were at higher levels immediately before and especially during the transition to widowhood, and increased at a steeper rate post-widowhood. Age and partially depressive symptoms accounted for these trends in ADL limitations pre-widowhood and to a lesser extent during the transition to widowhood and post-widowhood. Older age, being female, chronic conditions, financial strain, lower educational attainment, coresidence with children and others, and less frequent church attendance were risk factors for higher levels of and greater increases in these functional limitations throughout widowhood experience.     

Trajectories of Interracial Heterosexual Couples: A Longitudinal Analysis of Relationship Quality and Separation

Minimal research has examined interracial couples’ relationship satisfaction and dissolution patterns over time. Using dyadic data across 8 years, we examined potential differences in relationship quality trajectories through latent growth curve modeling with 1,336 couples as well as differential risks for relationship dissolution through logistic regression between same‐race and interracial relationships using a different subset of 2,370 couples. Results indicated that women in interracial relationships were significantly lower in initial relationship quality than women in same‐race relationships. Further, interracial couples of Black‐Hispanic partnerings were twice as likely to separate across 8 years than same‐race couples. These results suggest that despite interracial relationships not substantively differing from same‐race couples in trajectories of relationship quality, specific Black‐Hispanic interracial couples are at a higher risk of eventual separation.