Bootstrap order selection for SETAR models

In this paper, we investigate the selecting performances of a bootstrapped version of the Akaike information criterion for nonlinear self-exciting threshold autoregressive-type data generating processes. Empirical results will be obtained via Monte Carlo simulations. The quality of our method is assessed by comparison with its non-bootstrap counterpart and through a novel procedure based on artificial neural networks.     

Earthquakes occurrences estimation through a parametric semi-Markov approach

The estimation of earthquakes’ occurrences prediction in seismic areas is a challenging problem in seismology and earthquake engineering. Indeed, the prevention and the quantification of possible damage provoked by destructive earthquakes are directly linked to this kind of prevision. In our paper, we adopt a parametric semi-Markov approach. This model assumes that a sequence of earthquakes is seen as a Markov process and besides it permits to take into consideration the more realistic assumption of events’ dependence in space and time. The elapsed time between two consecutive events is modeled as a general Weibull distribution. We determine then the transition probabilities and the so-called crossing states probabilities. We conclude then with a Monte Carlo simulation and the model is validated through a large database containing real data.     

BL-GARCH models with elliptical distributed innovations

In this work, we discuss the class of bilinear GARCH (BL-GARCH) models that are capable of capturing simultaneously two key properties of non-linear time series: volatility clustering and leverage effects. It has often been observed that the marginal distributions of such time series have heavy tails; thus we examine the BL-GARCH model in a general setting under some non-normal distributions. We investigate some probabilistic properties of this model and we conduct a Monte Carlo experiment to evaluate the small-sample performance of the maximum likelihood estimation (MLE) methodology for various models. Finally, within-sample estimation properties were studied using S&P 500 daily returns, when the features of interest manifest as volatility clustering and leverage effects. The main results suggest that the Student-t BL-GARCH seems highly appropriate to describe the S&P 500 daily returns.     

Social development quartet: When is parental supportiveness a good thing? The dynamic value of parents' supportive emotion socialization across childhood

This introduction to the Social Development Quartet summarizes four articles that examine age‐related and contextual shifts in the utility of parents' emotion socialization responses for children's social‐emotional development. The first two articles present evidence for age‐related changes in the benefits of parents' supportive responses and consequences of parents' nonsupportive responses to children's negative emotions between early and middle childhood. The next two articles consider contextual variations in this developmental shift by examining teacher reports of children's competence and family patterns of response among mothers and fathers. Together, these studies question the unilateral assumption that parental support of children's negative emotions is always a good thing, and provide a more nuanced understanding of when and in what contexts parents' responses are adaptive for children.     

汽车侧围外板尾翼拉延成型工艺改善研究

为解决汽车侧围外板尾翼在拉延成型后出现起皱和开裂的问题，设计了3种造型方案.通过造型设计分析及Autoform模拟，对比3种方案，对原工艺进行整改和优化，得到了抬高造型台阶面的最优造型方案.该方案能改善进料速度、增加材料流动性，有效地消除开裂、起皱的缺陷，对同类和其他类似产品的冲压工艺设计具有参考意义.     

Social identity and alcohol in young adolescence: the perceived difference between youthful and adult drinking

This paper examines the evolving social identities of young adolescents in regard to alcohol and drinking culture in Norway. Detailed analysis of 29 focus group interviews and 32 individual interviews with 12–13-year-olds reveal a thorough negative attitude towards alcohol, especially when enjoyed by young people. Young adolescents found young people to be too irresponsible and immature to drink, while adults were portrayed as capable of enjoying alcohol without losing control or experiencing other negative effects. Through symbolic boundary work, they distanced themselves from adolescents who drank. The young adolescents rejected the idea that drinking alcohol was a sign of maturity; instead, they exhibited maturity by distancing themselves from drunk adolescents. We discuss how these findings reflect the participants’ socio-cognitive development, and how symbolic boundaries are often drawn against those closest in social distance. We conclude that boundaries between ‘adolescents’ and ‘adults’ are fundamental when understanding emerging adolescent social identities, especially when it comes to drinking and drinking culture.     

Bayesian ratemaking under Dirichlet process mixtures

Experience ratemaking plays a crucial role in general insurance in determining future premiums of individuals in a portfolio by assessing observed claims from the whole portfolio. This paper investigates this problem in which claims can be modeled by certain parametric family of distributions. The Dirichlet process mixtures are employed to model the distributions of the parameters so as to make two advantages: to produce exact Bayesian experience premiums for a class of premium principles generated from generic error functions and, at the same time, provide robust and flexible ways to avoid possible bias caused by traditionally used priors such as non informative priors or conjugate priors. In this paper, the Bayesian experience ratemaking under Dirichlet process mixture models are investigated and due to the lack of analytical forms of the conditional expectations of the quantities concerned, the Gibbs sampling schemes are designed for the purpose of approximations.     

Hypothesis Testing in a Rayleigh Diffusion Model

Applying the large and moderate deviations for the log-likelihood ratio of the Rayleigh diffusion model, we give the negative regions in testing Rayleigh diffusion model and obtain the decay rates of the error probabilities.     

An EWMA chart for monitoring process mean

In the statistical process control literature, there exists several improved quality control charts based on cost-effective sampling schemes, including the ranked set sampling (RSS) and median RSS (MRSS). A generalized cost-effective RSS scheme has been recently introduced for efficiently estimating the population mean, namely varied L RSS (VLRSS). In this article, we propose a new exponentially weighted moving average (EWMA) control chart for monitoring the process mean using VLRSS, named the EWMA-VLRSS chart, under both perfect and imperfect rankings. The EWMA-VLRSS chart encompasses the existing EWMA charts based on RSS and MRSS (named the EWMA-RSS and EWMA-MRSS charts). We use extensive Monte Carlo simulations to compute the run length characteristics of the EWMA-VLRSS chart. The proposed chart is then compared with the existing EWMA charts. It is found that, with either perfect or imperfect rankings, the EWMA-VLRSS chart is more sensitive than the EWMA-RSS and EWMA-MRSS charts in detecting small to large shifts in the process mean. A real dataset is also used to explain the working of the EWMA-VLRSS chart.     

Non uniform exponential bounds on normal approximation by Stein’s method and monotone size bias couplings

It is known that the normal approximation is applicable for sums of non negative random variables, W, with the commonly employed couplings. In this work, we use the Stein’s method to obtain a general theorem of non uniform exponential bound on normal approximation base on monotone size bias couplings of W. Applications of the main result to give the bound on normal approximation for binomial random variable, the number of bulbs on at the terminal time in the lightbulb process, and the number of m runs are also provided.