On asymptotic posterior normality for controlled branching processes

For a controlled branching process (CBP) with offspring distribution belonging to the power series family, the asymptotic normality of the posterior distribution of the basic parameter and the offspring mean is proved. As practical applications, we calculate asymptotic high probability density credibility sets for the offspring mean and we provide a rule to make inference about the value of this parameter. Moreover, the asymptotic posterior normality of the respective parameters of two classical branching models, namely the standard Galton–Watson process and the Galton–Watson process with immigration, is derived as particular cases of the CBP.     

Testing Monotonicity of Regression Functions – An Empirical Process Approach

We propose several new tests for monotonicity of regression functions based on different empirical processes of residuals and pseudo‐residuals. The residuals are obtained from an unconstrained kernel regression estimator whereas the pseudo‐residuals are obtained from an increasing regression estimator. Here, in particular, we consider a recently developed simple kernel‐based estimator for increasing regression functions based on increasing rearrangements of unconstrained non‐parametric estimators. The test statistics are estimated distance measures between the regression function and its increasing rearrangement. We discuss the asymptotic distributions, consistency and small sample performances of the tests.     

Strong approximation of empirical copula processes by Gaussian processes

In this paper, we provide the strong approximation of normalized empirical copula processes by a Gaussian process. In addition, we establish a strong approximation of the smoothed empirical copula processes and a law of iterated logarithm.     

Classes of diffusion-type processes with a sufficient reduction

Classes of processes of the diffusion type permitting a sufficient data reduction are derived. None of these classes are exponential families in the usual sense. For one type of such classes the sufficient statistic equals that of a curved exponential family of diffusion-type processes. For a second type the last observation is sufficient. In particular cases both types of classes are defined by means of a RICCATI equation     

Robust Correlation Structure for Multivariate Failure Time Data

When incomplete repeated failure times are collected from a large number of independent individuals, interest is focused primarily on the consistent and efficient estimation of the effects of the associated covariates on the failure times. Since repeated failure times are likely to be correlated, it is important to exploit the correlation structure of the failure data in order to obtain such consistent and efficient estimates. However, it may be difficult to specify an appropriate correlation structure for a real life data set. We propose a robust correlation structure that can be used irrespective of the true correlation structure. This structure is used in constructing an estimating equation for the hazard ratio parameter, under the assumption that the number of repeated failure times for an individual is random. The consistency and efficiency of the estimates is examined through a simulation study, where we consider failure times that marginally follow an exponential distribution and a Poisson distribution is assumed for the random number of repeated failure times. We conclude by using the proposed method to analyze a bladder cancer dataset.     

Interprofessional collaboration between residential child care and mental care practitioners: a cross-country study in six European countries

ABSTRACT

The severe mental health problems of many of the young people living in residential settings pose a great challenge and demand on child protection and mental care (MC) services. Drawing on comparative research and debates from six European countries, this study examines demands for integrated care and interprofessional collaboration practices between residential child care (RCC) and MC. In this article, research data will be brought together from Denmark, Finland, Germany, Lithuania, the UK (Scotland) and Spain. In total, 61 practitioners from RCC and MC were interviewed. Given the complexity of the residential care service context and service system differences across national contexts, the original hypothesis was that this would differentiate the collaboration practices. However, the similarity between the countries is greater than anticipated. The concluding findings are organised by matrix technique into a content-analytic summary table. The main finding was that in spite of encouragement for integrated RCC, obstacles for collaboration and lack of coordination between systems remain, often related to understanding the professional role and tasks, lack of shared knowledge, attitudes and ways of communication. One significant finding in the cross-country comparison was the evident and unrealistic expectations for the ‘other’ provider to help and care.     

Family Processes and Children's and Adolescents' Well-Being

The primary purpose of this review was to examine theory and research published during the past decade that focused on family processes and children's and adolescents' well-being. Scholarship focused on family processes and child and adolescent well-being made significant and exciting advances during this decade based on several key advancements. In addition to a brief introduction and a conclusion, this decade in review is organized into four sections. In the first section, advances made in the literature because of increased attention to complexity and specificity are illustrated. The second section describes advances that were made because of increased attention to family processes in diverse families. Diversity in the samples of families studied, extensions in family process models, and the revisioning of grand theories using a diversity lens that were used to conceptualize family processes are detailed. In the third section, the importance of time in the study of family processes and child and adolescent well-being is described. The emphasis on families' daily lives is noted. In addition, prospective considerations and studies of change over time are highlighted. Strengths in family functioning are detailed in the fourth section of this article: positivity, regulatory processes, and family organization. These three areas were selected to elaborate the idea that one of the major advancements in the family process literature during the past decade was an emphasis on family strengths. This review concludes with a commentary regarding how conceptual and methodological advancements during the past decade can guide future scholarship.     

Tiered Approach to Resilience Assessment

Regulatory agencies have long adopted a three‐tier framework for risk assessment. We build on this structure to propose a tiered approach for resilience assessment that can be integrated into the existing regulatory processes. Comprehensive approaches to assessing resilience at appropriate and operational scales, reconciling analytical complexity as needed with stakeholder needs and resources available, and ultimately creating actionable recommendations to enhance resilience are still lacking. Our proposed framework consists of tiers by which analysts can select resilience assessment and decision support tools to inform associated management actions relative to the scope and urgency of the risk and the capacity of resource managers to improve system resilience. The resilience management framework proposed is not intended to supplant either risk management or the many existing efforts of resilience quantification method development, but instead provide a guide to selecting tools that are appropriate for the given analytic need. The goal of this tiered approach is to intentionally parallel the tiered approach used in regulatory contexts so that resilience assessment might be more easily and quickly integrated into existing structures and with existing policies.     

Convergence de I estimateur a noyau de derivees de Radon-Nikodym generales dans le cas melangeant

In many situations, nonparametric inference in point-process theory consists in estimating a Radon-Nikodym derivative of a nonnegative measure p with respect to another nonnegative measure v, where p and v are intensities of point processes. We consider the case of a mixing andstrictly stationary sequence of point processes and establish convergence results for the kernel estimator.