野性斯派塞

<正>苍绿的草原一望无际,起伏的山丘上搭着一道道浓绿的葡萄架,远处成群的牛羊悠闲地吃着草,星星点点的白色房屋,好似一幅静美的天然油画,而澳大利亚五星级牧场斯派塞就坐落于这绿色深处。     

A Multistate Transition Model for Osteoarthritis Pain Change

Pain severity of knees is assessed using an ordinal scale in patients with musculoskeletal diseases and often changes over time. Assessment of the effect of a particular risk factor on the change in pain severity will shed light on our understanding of biological mechanisms and provide guidance for rational clinical intervention for recurrent pain. The multistate transition model allows transitions between several different states of pain severity and estimates the transitional intensity using an extension of the Cox proportional hazards model. Using data from a longitudinal study, we applied this model to assess the relation of two psychological factors to the change in knee pain severity over time among patients with osteoarthritis and demonstrated that the multistate transition model can be a valuable tool for rheumatic disease studies.     

钛酸锶钡溶胶制备研究

用锶、钡的有机酸盐和钛酸丁酯为原料,以溶胶-凝胶法制备了钛酸锶钡溶皎。考察了有机酸分子量、溶胶的水解方法对溶胶亲润性、湿敏性、二氧化碳敏感性、成膜均匀性、热解性等的影响。实验得出:先将钛酸丁酯的乙酸乙酯溶液部分水解,然后与锶、钡的正辛酸盐、2-乙基己酸盐或壬酸盐的乙酸乙酯溶液充分混合,所得的溶胶具有较好的综合性能。     

Detecting structural change in linear models

Consider a sequence of independent observations which change their marginal distribution at most once somewhere in the sequence and one is not certain where the change has occurred. One would be interested in detecting the change and determining the two distributions which would describe the sequence. On the other hand if no change had occurred, one would want to know the common distribution of the observations. This study develops a Bayesian test for detecting a switch from one linear model to another. The test is based on the marginal posterior mass function of the switch point and the posterior probability of a stable model. This test and an informal sequential procedure of Smith are illustrated with data generated from an unstable linear regression model, which changes the linear relationship between the dependent and independent variables     

光·影

<正>"百般光华千色暗,一盏瓷胎万彩生。"Oriental Danny纯手工精心制作的陶瓷艺术品同灯光相遇,光华流转,映照这纤秾合度的釉彩瓷胎,若隐若现,披     

Robust Bayesian analysis of loss reserving data using scale mixtures distributions

It is vital for insurance companies to have appropriate levels of loss reserving to pay outstanding claims and related settlement costs. With many uncertainties and time lags inherently involved in the claims settlement process, loss reserving therefore must be based on estimates. Existing models and methods cannot cope with irregular and extreme claims and hence do not offer an accurate prediction of loss reserving. This paper extends the conventional normal error distribution in loss reserving modeling to a range of heavy-tailed distributions which are expressed by certain scale mixtures forms. This extension enables robust analysis and, in addition, allows an efficient implementation of Bayesian analysis via Markov chain Monte Carlo simulations. Various models for the mean of the sampling distributions, including the log-Analysis of Variance (ANOVA), log-Analysis of Covariance (ANCOVA) and state space models, are considered and the straightforward implementation of scale mixtures distributions is demonstrated using OpenBUGS.     

Bridging Adaptive Learning and Desired Natural Resource Management Outcomes: Insights from Australian Planners

Natural resource management (NRM) has been increasingly guided by governance arrangements seeking less centralized and hierarchical and more integrated and adaptive approaches to achieve desired social-ecological outcomes. Successful implementation of these approaches requires adaptive learning which entails the application of individual, institutional and social learning to adaptive co-management. This paper proposes and validates a conceptual model that identifies components of adaptive learning and their relationships with desired NRM outcomes. Supported by on-ground experience of Australian NRM planners, it discusses three key insights to enable bridging between adaptive learning and NRM outcomes: changing focus away from economic-efficiency culture, supporting learning and knowledge exchange structures, and reinventing practice.     

Online political public relations as a place-based relational practice: A cultural discourse perspective

This study introduces the theoretical and methodological approach of Carbaugh’s (2007) cultural discourse analysis (CuDA) to advance the research agenda on political public relations. I discuss how CuDA, as an extension of the ethnography of communication (EoC), provides clues to unexpected success in an election campaigning. Using the 2016 Hong Kong lawmakers’ election as an empirical example, the most discussed Facebook posts of an election candidate, and 6800 online comments from the public are studied. I identify the socio-cultural meanings that are used and can be used to engage public-to-public election canvassing. This study shows that the prominent discursive hubs of dwelling and relation organize networked publics to canvass. Responding to the socio-cultural turn of the literature, this study grounds the theorization of political public relations in practice. The evaluation of different approaches to discourse also moves the field forward methodologically.     

Modelling stochastic volatility using generalized t distribution

In modelling financial return time series and time-varying volatility, the Gaussian and the Student-t distributions are widely used in stochastic volatility (SV) models. However, other distributions such as the Laplace distribution and generalized error distribution (GED) are also common in SV modelling. Therefore, this paper proposes the use of the generalized t (GT) distribution whose special cases are the Gaussian distribution, Student-t distribution, Laplace distribution and GED. Since the GT distribution is a member of the scale mixture of uniform (SMU) family of distribution, we handle the GT distribution via its SMU representation. We show this SMU form can substantially simplify the Gibbs sampler for Bayesian simulation-based computation and can provide a mean of identifying outliers. In an empirical study, we adopt a GT–SV model to fit the daily return of the exchange rate of Australian dollar to three other currencies and use the exchange rate to US dollar as a covariate. Model implementation relies on Bayesian Markov chain Monte Carlo algorithms using the WinBUGS package.