BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.     

Proportional reversed hazard rate model and its applications

The purpose of this paper is to study the structure and properties of the proportional reversed hazard rate model (PRHRM) in contrast to the celebrated proportional hazard model (PHM). The monotonicity of the hazard rate and the reversed hazard rate of the model is investigated. Some criteria of aging are presented and the inheritance of the aging notions (of the base distribution) by the PRHRM is studied. Characterizations of the model involving Fisher information are presented and the statistical inference of the parameters is discussed. Finally, it is shown that several members of the proportional reversed hazard rate class have been found to be useful and flexible in real data analysis.     

HEAVY-TAILED-DISTRIBUTED THRESHOLD STOCHASTIC VOLATILITY MODELS IN FINANCIAL TIME SERIES

To capture mean and variance asymmetries and time‐varying volatility in financial time series, we generalize the threshold stochastic volatility (THSV) model and incorporate a heavy‐tailed error distribution. Unlike existing stochastic volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time‐delay parameter. Self‐exciting and exogenous threshold variables are considered to investigate the impact of a number of market news variables on volatility changes. Adopting a Bayesian approach, we use Markov chain Monte Carlo methods to estimate all unknown parameters and latent variables. A simulation experiment demonstrates good estimation performance for reasonable sample sizes. In a study of two international financial market indices, we consider two variants of the generalized THSV model, with US market news as the threshold variable. Finally, we compare models using Bayesian forecasting in a value‐at‐risk (VaR) study. The results show that our proposed model can generate more accurate VaR forecasts than can standard models.     

Horwitz's rule, transforming both sides and the design of experiments for mechanistic models

Summary. The paper develops methods for the design of experiments for mechanistic models when the response must be transformed to achieve symmetry and constant variance. The power transformation that is used is partially justified by a rule in analytical chemistry. Because of the nature of the relationship between the response and the mechanistic model, it is necessary to transform both sides of the model. Expressions are given for the parameter sensitivities in the transformed model and examples are given of optimum designs, not only for single-response models, but also for experiments in which multivariate responses are measured and for experiments in which the model is defined by a set of differential equations which cannot be solved analytically. The extension to designs for checking models is discussed.     

Fundamentals of Theory and Practice Revisited; The Mutiny and the Bounty: The Place of Milan Ideas Today

The author traces the development of the Milan approach from the beginning, through the split into two teams in 1980, and subsequent developments in theory and application. He identifies possible unrecognised or undeclared influences of Milan in other family therapy approaches.     

Estimation of Metabolic Rate Constants in PBPK‐Models from Liver Slice Experiments: What Are the Experimental Needs?

A mechanistic model is presented describing the clearance of a compound in a precision-cut liver slice that is incubated in a culture medium. The problem of estimating metabolic rate constants in PBPK models from liver slice experiments is discussed using identifiability analysis. From the identifiability problem analysis, it appears that in addition to the clearance, the compound's free fraction in the slice and the diffusion rate of the exchange of the compound between culture medium and liver slice should be identified. In addition, knowledge of the culture medium volume, the slice volume, the compound's free fraction, and octanol-water-based partition between medium and slice is presupposed. The formal solution for identification is discussed from the perspective of experimental practice. A formally necessary condition for identification is the sampling of parent compound in liver slice or culture medium. However, due to experimental limitations and errors, sampling the parent compound in the slice together with additional sampling of metabolite pooled from the medium and the slice is required for identification in practice. Moreover, it appears that identification results are unreliable when the value of the intrinsic clearance exceeds the value of the diffusion coefficient, a condition to be verified a posteriori.     

The effects of language on judgments of universal facial expressions of emotion

Because of the close connection between culture and language, a number of writers have suggested that bilinguals will differ in their behavior because of differences in the degree of assimilation of different cultures in the same individual. We tested this notion by obtaining data from bilingual (English and Hindi) college students in India using a well-studied cross-cultural research paradigm involving emotional perception. Subjects judged universal facial expressions of emotion in two separate sessions, one conducted entirely in English, the other in Hindi. In each session, they judged which emotion was being portrayed, and how intensely. Subjects recognized anger, fear, and sadness more accurately in English than in Hindi. They also attributed greater intensity to female photos of anger when rating in Hindi, but attributed greater intensity to female photos of sadness when rating in English. These findings were discussed in relation to the theoretical connection between culture and language.     

Vulnerability and Agenda: Context and Process in Project Management

This paper explores how the project management role is conditioned by the context in which change is progressed. The argument draws on Pettigrew's (1985, 1987) contextual and processual view of change, a view which does not clarify the management implications of contextual variation. Using data from a two-stage research design combining diary and survey methods, four context dimensions are identified, concerning ‘interlocking’, ‘shifting sands’, ‘ownership’ and ‘senior management view’. For analytical purposes, two extreme contexts are characterized as exposing the project manager to high and low levels of ‘vulnerability’ respectively. Project management literature typically offers a rational-linear account of change, and concentrates on ‘content’ and ‘control’ agendas, concerning technical expertise on the one hand, and planning, budgeting and monitoring techniques on the other. Sociological analyses reveal the limitations of the rational-linear account, and focus on the political and cultural dimensions of the ‘process’ agenda. The data suggest how contextual variation affects the relative priority of these agendas. The management implications of these findings are explored, for project management selection, career progression, and the development of diagnostic skills and ‘agenda management’ strategies.