基于EMD与DVG的非线性时间序列预测模型及其应用研究

针对具有非线性和不稳定性的时间序列,提出一种结合经验模态分解(EMD)、有向可见图(DVG)网络的动态预测模型。利用经验模态分解将原时间序列分解为多个固有模态函数(IMF),然后对分解后的高频和低频IMF利用快速傅里叶变换得到各自的周期;依据每个周期,从原时间序列的尾部截取长短不一的子序列,然后采用有向可见图算法转换为多个有向网络,利用随机游走在每个有向网络中寻找与时间序列最后一个节点相似的节点;最后,依据平行线法,预测时间序列的下一个数值。原油价格的时间序列是一类典型的具有非线性和不稳定性的序列,利用此模型对WTI原油每日价格进行实证分析。研究结果表明,此模型不但可以有效地预测时间序列的变化趋势,而且具有较高的预测精度。     

Some results on bootstrap prediction intervals

We investigate the construction of a BC_a-type bootstrap procedure for setting approximate prediction intervals for an efficient estimator θ_m of a scalar parameter θ, based on a future sample of size m. The results are also extended to nonparametric situations, which can be used to form bootstrap prediction intervals for a large class of statistics. These intervals are transformation-respecting and range-preserving. The asymptotic performance of our procedure is assessed by allowing both the past and future sample sizes to tend to infinity. The resulting intervals are then shown to be second-order correct and second-order accurate. These second-order properties are established in terms of min(m, n), and not the past sample size n alone.     

Approximation spline de la prevision d'un processus fonctionnel autorégressif d'ordre 1

ABSTRACT We present a method to approximate and forecast, on an entire interval, a continuous-time process. For this purpose, we use the modelization of ARH(l) processes, defined by Bosq (1991). We deal with the practical problem of the discretization of the observed trajectories and approximate them by means of spline functions. We show by simulations that for well-chosen smoothing parameters, good prediction can be obtained in comparison with the “predictable” part of the process. Finally, we apply this model to forecast road traffic and compare it with a SARIMA model.     

Nonparametric estimation of discrete hazard functions

A smoothing procedure for discrete time failure data is proposed which allows for the inclusion of covariates. This purely nonparametric method is based on discrete or continuous kernel smoothing techniques that gives a compromise between the data and smoothness. The method may be used as an exploratory tool to uncover the underlying structure or as an alternative to parametric methods when prediction is the primary objective. Confidence intervals are considered and alternative techniques of cross validation based choices of smoothing parameters are investigated.     

A proposed methodology for the prediction of mental workload, based on engineering system parameters

In the design of engineering systems, mental workload is one of the most important factors in the allocation of cognitive tasks. Current methods of task allocation have criteria that are defined in only general terms and are thus not very useful in aiding detailed decision-making in system design. Whilst there are many quantitative criteria available to determine the physical space in human-machine interaction, system designers really require an explicit model and specific criteria for the following identification of the mental workload imposed by the system; prediction of both human and system performance; evaluation of the alternatives of system design; and the design of system components. It is argued that the available methods of workload or performance are either too domain-dependent to apply to the design of other systems, or subject-dependent and thus do not reflect the objective workload imposed by the system. The presented research adopts a new approach to cognitive task analysis in dynamic decision-making systems. Based on the characteristics derived from task analysis, a general conceptual model of the prediction of mental workload in system design is proposed. In the new model, workload is represented by a set of system parameters—task arrival rate, task complexity, task uncertainty, and performance requirements—which are considered to be the main sources of workload. In this context, workload becomes an objective demand of engineering systems, independent of any subjective factors. Whether an individual or population is overloaded depends upon their workload threshold with respect to the specified task and environment. It is hoped that this new model, after both laboratory and industrial validation, could be used by system designers to predict the workload imposed on people by systems.     

Aggressive Behaviors in Social Interaction and Developmental Adaptation: A Narrative Analysis of Interpersonal Conflicts During Early Adolescence

Using conflict narratives reported by adolescents in grade 7 (mean age = 13.4 years), this study investigated the interactional properties and developmental functions of four types of aggressive behaviors: social aggression, direct relational aggression, physical aggression, and verbal aggression. A total of 475 participants from the Carolina Longitudinal Study ( Cairns & Cairns, 1994 ) were included. Results showed that the majority of conflict interactions involved more than a dyad. The use of social aggression (e.g., concealed social attack) was associated with more individuals involved in the conflict. Social aggression was primarily reported as an initiating behavior for interpersonal conflicts, while direct relational aggression was a responding behavior. Medium to high levels of reciprocity were found for physical, verbal, and direct relational aggression, whereas a low level of reciprocity was reported for social aggression. School authorities were most likely to intervene in physical aggression. The use of social aggression was associated with higher network centrality among adolescents. Developmental maladjustment in late adolescence and early adulthood was primarily predicted by physical aggression.     

Some large trial properties of minimum likelihood allocation

The method of minimum likelihood allocation (MLA) for allocating subjects to treatments in a clinical trial amounts to checking at each stage which allocation would lead an outside observer to find the least evidence of a relationship between treatment and factors of prognostic significance, assuming that the observer would use a linear exponential model. One advantage of MLA is that results from game theory and likelihood theory can be used to prove it has desirable long run properties. Two of these demonstrated here are (1) ‘consistency’, in the sense that the average likelihood ratio which measures design imbalance tends to zero, and (2) ‘efficiency’ in the sense that the variance estimates of treatment effects will tend to be minimized in the long run.     

Inference about permutation parameter in large samples

The estimation problem of a permutation parameter on the basis of a random sample of increasing size is considered. A necessary and sufficient condition for the existence of an estimator, asymptotically fully efficient for two different distributions families, is derived. We also study the application of this result to cyclic groups of order two and three.