Probability Generating Function Based Jeffrey's Divergence for Statistical Inference

Statistical inference procedures based on transforms such as characteristic function and probability generating function have been examined by many researchers because they are much simpler than probability density functions. Here, a probability generating function based Jeffrey's divergence measure is proposed for parameter estimation and goodness-of-fit test. Being a member of the M-estimators, the proposed estimator is consistent. Also, the proposed goodness-of-fit test has good statistical power. The proposed divergence measure shows improved performance over existing probability generating function based measures. Real data examples are given to illustrate the proposed parameter estimation method and goodness-of-fit test.     

Open Dialogue: Frequently Asked Questions

Open Dialogue is an approach to working with people and their families experiencing psychosocial distress. Interest in Open Dialogue in Australia has been growing recently, raising questions about its adaption and implementation to local contexts. This article is an attempt to answer some of the frequently asked questions we have encountered in training and discussions about Open Dialogue. We attempt to provide responses to questions of how Open Dialogue is different to what is done already, how it fits with current approaches, how you know if you are doing it, whether it is passive or just about doing reflections, issues about including the social network, and concerns about the evidence base. This article aims to present a variety of viewpoints in relation to these questions and to hopefully further discussions on how Open Dialogue can be implemented and adapted to Australian health care and social care contexts.     

Networks for Welfare Provision: Getting a Grip on Processes of Social Exclusion by Evaluating Network Effectiveness

It has been repeatedly stated that the topic of network effectiveness has often been neglected. This has led to a situation of ‘network euphoria’ amongst practitioners and policymakers with regard to the creation of networks as a means to (re‐)organize welfare provision. Starting from a case study of networks for welfare provision in two Belgian cities, this article focuses on the effectiveness of service delivering networks at the client level, which is understood as the contribution of the network in improving the conditions of life of those being served or targeted by the network. Therefore, we focused on the collective efforts via these networks (e.g. by creating a night shelter or by conducting case consultations) to look after a population of homeless people who face multiple problems and are not able yet to benefit from welfare provision. Our findings revealed that these networks were able to realize a ‘collaborative advantage’ by filling in service gaps and by overcoming fragmentation of care. Nevertheless, these networks equally maintained criteria that restricted the accessibility or usefulness of welfare services provided to homeless people. In the concluding section, we highlight some of the factors that could help us to explain our findings and highlight the tension between the effectiveness of networks at the client level and the effectiveness at the organizational level.     

Children's Presence in the Neighbourhood: A Social‐Pedagogical Perspective

In this article we discuss some theoretical and methodological perspectives for studying children's neighbourhoods as a social‐pedagogical context. This social‐pedagogical perspective includes a focus in research on a reflective approach based on the acquisition of empirical indicators about the impact of the neighbourhood on children's socialisation. A research outline based on the idea of mapping children's neighbourhoods within their social and historical context is presented as one possible example of such an analysis.     

人工冻土冻胀及其抑制研究述评

人工冻结冻施工技术是岩土工程尤其是特殊地质和工程条件下地下工程施工的重要方法之一，但冻胀现象制约了该方法的推广应用。从人工冻土冻胀的影响因素、物理模拟概况、数值模拟现状及冻胀抑制等方面总结归纳了国内外在冻胀及其抑制上的研究成果。     

Establishing self and meaning in low back pain narratives

Pain narratives encounter the problem of verbalising private and internalised experiences. Words appear to fall short of giving meaning to the feelings and impact of pain. In this paper we report on how people describe their low back pain and the way in which they claim to present this to clinicians. In the research interviews they need to establish themselves as believable narrators and provide accounts of how they legitimise their pain in clinical encounters. As a result, the interviews provide complex and layered narratives of pain and its representation.     

A Lagrangian Non Central Negative Binomial Distribution of the First Kind

A Lagrangian probability distribution of the first kind is proposed. Its probability mass function is expressed in terms of generalized Laguerre polynomials or, equivalently, a generalized hypergeometric function. The distribution may also be formulated as a Charlier series distribution generalized by the generalizing Consul distribution and a non central negative binomial distribution generalized by the generalizing Geeta distribution. This article studies formulation and properties of the distribution such as mixture, dispersion, recursive formulas, conditional distribution and the relationship with queuing theory. Two illustrative examples of application to fitting are given.     

Parameter estimation by minimizing a probability generating function-based power divergence

Abstract

Generating function-based statistical inference is an attractive approach if the probability (density) function is complicated when compared with the generating function. Here, we propose a parameter estimation method that minimizes a probability generating function (pgf)-based power divergence with a tuning parameter to mitigate the impact of data contamination. The proposed estimator is linked to the M-estimators and hence possesses the properties of consistency and asymptotic normality. In terms of parameter biases and mean squared errors from simulations, the proposed estimation method performs better for smaller value of the tuning parameter as data contamination percentage increases.