Asymptotic robustness of least median of squares for autoregressions with additive outliers

This paper considers the robustness properties in the time series context of the least median of squares (LMS) estimator. The influence function of the LMS estimator is derived under additive outlier contamination. This influence function is redescending and bounded for fixed values of the AR parameters. The gross-error sensitivity, however, is an unbounded function of the AR parameters. In order to asses the global robustness behavior of the LMS estimator, we consider several notions of breakdown. The breakdown points of the LMS estimator depend on the value of the underlying AR parameter. Generally, the breakdown point is below one half for high values of the AR parameter. The bias curves of the LMS estimator reveal, however, that the magnitude of outliers has to be considerable in order to cause breakdown.     

Central Limit Theorem approximations for the number of runs in Markov-dependent binary sequences

We consider Markov-dependent binary sequences and study various types of success runs (overlapping, non-overlapping, exact, etc.) by examining additive functionals based on state visits and transitions in an appropriate Markov chain. We establish a multivariate Central Limit Theorem for the number of these types of runs and obtain its covariance matrix by means of the recurrent potential matrix of the Markov chain. Explicit expressions for the covariance matrix are given in the Bernoulli and a simple Markov-dependent case by expressing the recurrent potential matrix in terms of the stationary distribution and the mean transition times in the chain. We also obtain a multivariate Central Limit Theorem for the joint number of non-overlapping runs of various sizes and give its covariance matrix in explicit form for Markov dependent trials.     

Improving traceability in continuous processes using flow simulations

Traceability is normally difficult to achieve in continuous processes, since there are no natural batch structures. In this article, we demonstrate flow-based simulation using process data to improve traceability in a continuous pelletising process. Using the simulation model, the engineers could test the impacts of process disturbances, identify cause and effect relations and aid control in case of process disturbances. In a field trial where the chemistry of an additive was varied during production of a special product, the simulation forecasts predicted the level of the chemical content after the plant within the errors that the engineers found acceptable.     

OPTIMAL SOFTWARE RELEASE POLICY BASED ON MARKOVIAN PERFECT DEBUGGING MODEL

In this paper we consider a Markovian perfect debugging model for which the software failure is caused by two types of faults, one which is easily detected and the other which is difficult to detect. When a failure occurs, a perfect debugging is immediately performed and consequently one fault is reduced from fault contents. We also treat the debugging time as a variable to develop a new debugging model. Based on the perfect debugging model, we propose an optimal software release policy that satisfies the requirements for both software reliability and expected number of faults which are required to achieve before releasing the software. Several measures, including the distribution of first passage time to the specified number of removed faults, are also obtained using the proposed debugging model.     

The role of time perspective in predicting Iranian farmers’ participatory-based water conservation attitude and behavior

ABSTRACT

In current perspective, farmers’ participatory behavior toward conservation of water resources (FPBCWR) is one of the most important strategies under water resource management in rural Iran. In this regard, understanding the predictors of farmers’ participatory-based water conservation behaviors and attitudes is gaining more importance than earlier. Among different dimensions of farmers’ participatory behavior, the potential of temporal frames was examined rarely. Thus, 322 Iranian farmers were investigated to examine the potential of their time perspectives in predicting their participatory-based water conservation behavior and attitude. According to the study results, the effects of present orientation on attitude and behavior were negatively significant, while the effects of future orientation on attitude and behavior were positively significant, whereas its effects (path coefficients) were stronger than present orientation effects. Past orientation did not have a significant effect on attitude, though attitude positively and significantly affected farmers’ participatory behavior. The results of causal analysis revealed that presented model accounted for 58% of variance in farmers’ ‘behavior’ and 42% of variance in “attitude.” In conclusion, a few demonstrable illustrations of policy implications are presented to enable utilizing the important findings and concluding results of this study that is linked further with water resource management domain.     

Simulation of the p-generalized Gaussian distribution

In this paper, we introduce the p-generalized polar methods for the simulation of the p-generalized Gaussian distribution. On the basis of geometric measure representations, the well-known Box–Muller method and the Marsaglia–Bray rejecting polar method for the simulation of the Gaussian distribution are generalized to simulate the p-generalized Gaussian distribution, which fits much more flexibly to data than the Gaussian distribution and has already been applied in various fields of modern sciences. To prove the correctness of the p-generalized polar methods, we give stochastic representations, and to demonstrate their adequacy, we perform a comparison of six simulation techniques w.r.t. the goodness of fit and the complexity. The competing methods include adapted general methods and another special method. Furthermore, we prove stochastic representations for all the adapted methods.     

歌德《威廉·迈斯特》中的教育思想

在18～19世纪欧洲社会变革的大背景下，分析了歌德《威廉·迈斯特》中的教育思想。分析认为，《威廉·迈斯特》作为教育／启悟小说，不仅追寻一种和谐健全的人性理想，而且思考了宗教信仰和人性关系；表达了歌德对教育实践的思考，即艺术是培养全面发展和和谐一致的人的一种手段，社会也不能束缚个人的发展。     

A segmented regime-switching model with its application to stock market indices

This paper evaluates the ability of a Markov regime-switching log-normal (RSLN) model to capture the time-varying features of stock return and volatility. The model displays a better ability to depict a fat tail distribution as compared with using a log-normal model, which means that the RSLN model can describe observed market behavior better. Our major objective is to explore the capability of the model to capture stock market behavior over time. By analyzing the behavior of calibrated regime-switching parameters over different lengths of time intervals, the change-point concept is introduced and an algorithm is proposed for identifying the change-points in the series corresponding to the times when there are changes in parameter estimates. This algorithm for identifying change-points is tested on the Standard and Poor's 500 monthly index data from 1971 to 2008, and the Nikkei 225 monthly index data from 1984 to 2008. It is evident that the change-points we identify match the big events observed in the US stock market and the Japan stock market (e.g., the October 1987 stock market crash), and that the segmentations of stock index series, which are defined as the periods between change-points, match the observed bear–bull market phases.     

On the improvement of one-sided S control charts

The most common charting procedure used for monitoring the variance of the distribution of a quality characteristic is the S control chart. As a Shewhart-type control chart, it is relatively insensitive in the quick detection of small and moderate shifts in process variance. The performance of the S chart can be improved by supplementing it with runs rules or by varying the sample size and the sampling interval. In this work, we introduce and study one-sided adaptive S control charts, supplemented or not with one powerful runs rule, for detecting increases or decreases in process variation. The properties of the proposed control schemes are obtained by using a Markov chain approach. Furthermore, a practical guidance for the choice of the most suitable control scheme is also provided.