Bayesian prediction for progressively censored data from the Burr model

Received: August 14, 2000; revised version: April 23, 2001     

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.     

基于行业细分的上市公司经营失败预警研究

依据文献本文构建了一套包括17个指标的经营失败预警指标体系,根据2001-2005年上市公司的财务报表数据,采用Logistic回归,在区分制造和非制造两类行业基础上建立企业经营失败的预警模型。研究显示,分行业预警模型不仅总体预测精度高于混合行业模型,而且犯一类错误的概率明显低于混合行业模型,大大降低预测风险,具有较高的推广价值。     

ANOMALIES, PROBINGS, INSIGHTS: KEN FOREMAN'S ROLE IN THE SAMPLING INFERENCE CONTROVERSY OF THE LATE 20TH CENTURY

This paper is based on the author's recollections of work done for and with E.K. Foreman, and later developments of that work. It describes most particularly the author's early intimations of the potential for using prediction models in survey sampling, the reasons why the use of such models, especially for inferential purposes, was so strongly resisted in the second half of the 20th century, the manner in which randomization and prediction inferences can be combined, and some advantages flowing from that combination.     

人才预测方法在高校人才预测中的应用

介绍了高校人才预测的方法和原则，并运用回归预测、灰色预测、马尔科夫预测等方法对某高校2005～2010年的专业人才数量和人才的学历结构进行了预测，预测结果符合人才发展规律，切实可行。     

Temporal Aggregation of Stationary and Non-stationary Continuous-Time Processes

Abstract.  We study the autocorrelation structure of aggregates from a continuous-time process. The underlying continuous-time process or some of its higher derivative is assumed to be a stationary continuous-time auto-regressive fractionally integrated moving-average (CARFIMA) process with Hurst parameter H . We derive closed-form expressions for the limiting autocorrelation function and the normalized spectral density of the aggregates, as the extent of aggregation increases to infinity. The limiting model of the aggregates, after appropriate number of differencing, is shown to be some functional of the standard fractional Brownian motion with the same Hurst parameter of the continuous-time process from which the aggregates are measured. These results are then used to assess the loss of forecasting efficiency due to aggregation.     

Corrected proof of the result of 'A prediction error property of the Lasso estimator and its generalization' by Huang (2003)

The Lasso achieves variance reduction and variable selection by solving an ?₁‐regularized least squares problem. Huang (2003) claims that ‘there always exists an interval of regularization parameter values such that the corresponding mean squared prediction error for the Lasso estimator is smaller than for the ordinary least square estimator’. This result is correct. However, its proof in Huang (2003) is not. This paper presents a corrected proof of the claim, which exposes and uses some interesting fundamental properties of the Lasso.     

人工神经网络在阜新工业经济预测中的应用

针对宏观经济预测的问题,由于实际情况错综复杂,各种预测模型的精确度都比较差,难以在实际中应用。为了解决这一问题,以阜新1985-2001年时间段的工业总产值为样本,分析了几种影响因素,依据BP神经网络模型的理论和方法,详细介绍了建模的过程,从而建立工业经济预测的模型,利用该模型对工业总产值进行了预测。     

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.     

ST公司预警误判与会计信息质量关系的经验研究

本文以ST公司预警的相关判别模型为基础,经验地揭示了会计报表信息质量对ST公司预警误判的影响。研究表明:我国ST公司预警误判的原因在很大程度上与会计报表信息质量有关。为此,本文建议加快具体会计准则颁布和实施步伐,不断强化审计责任和监管部门的责任,提高会计信息质量。