创业板高科技公司估值与定价

鉴于创业板高科技公司的高成长性,引入人力资本系数概念可以求出机构投资者对高科技公司股票的预估价格。在引入回拨机制下,通过研究利益相关方利益最大化时的期望,从而推导出利益均衡时高科技公司股票IPO（首次公开发行）的一个价格模型。研究表明：IPO定价不仅与IPO公司资产价值相关,而且与发行费用等参数有关;IPO价格和抑价程度均是机构投资者内部估值的增函数。     

基于计算—实验综合模型的啮合齿面关键摩擦特性参数反求研究

在齿轮传动动测实验的基础上,引入有限单元法多场耦合分析和反求技术,提出了面向工程的复杂齿轮传动摩擦多性态概念,建立了复杂齿轮传动的"计算—实验综合模型";利用该综合模型对不同润滑状况下齿面摩擦因数进行了合理的反求,解决了复杂曲面摩擦因数难于求解的问题。     

A synthetic control chart for the coefficient of variation

The coefficient of variation (CV) control chart has recently been introduced in the literature. Here, the salient features of this chart and the conforming run length chart are integrated to produce a synthetic coefficient of variation (SynCV) chart. The run length profile of the SynCV chart is numerically compared with the originally proposed chart and the upward EWMA-γ² chart. The SynCV chart outperforms the original CV chart, while the EWMA-γ² outperforms the SynCV chart for small increases in the CV. However, for large increases in the CV, the SynCV chart outperforms the EWMA-γ² chart.     

Randomization of Clusters Versus Randomization of Persons Within Clusters

Many experiments aim at populations with persons nested within clusters. Randomization to treatment conditions can be done at the cluster level or at the person level within each cluster. The latter may result in control group contamination, and cluster randomization is therefore oftenpreferred in practice. This article models the control group contamination, calculates the required sample sizes for both levels of randomization, and gives the degree of contamination for which cluster randomization is preferable above randomization of persons within clusters. Moreover, itprovides examples of situations where one has to make a choice between both levels of randomization.     

Small area estimation under random regression coefficient models

Statistical agencies are interested to report precise estimates of linear parameters from small areas. This goal can be achieved by using model-based inference. In this sense, random regression coefficient models provide a flexible way of modelling the relationship between the target and the auxiliary variables. Because of this, empirical best linear unbiased predictor (EBLUP) estimates based on these models are introduced. A closed-formula procedure to estimate the mean-squared error of the EBLUP estimators is also given and empirically studied. Results of several simulation studies are reported as well as an application to the estimation of household normalized net annual incomes in the Spanish Living Conditions Survey.     

Comparative Study of Robust Estimators Based on a Sensitivity Coefficient in Principal Component Analysis

This work is devoted to robust principal component analysis (PCA). We give a comparison between some multivariate estimators of location and scatter by computing the influence functions of the sensitivity coefficient ρ corresponding to these estimators, and the mean squared error (MSE) of estimators of ρ. The coefficient ρ measures the closeness between the subspaces spanned by the initial eigenvectors and their corresponding version derived from an infinitesimal perturbation of the data distribution.     

Performance of bartlett adjustment for certain likelihood ratio tests

The effectiveness of Bartlett adjustment, using one of several methods of deriving a Bartlett factor, in improving the chi-squared approximation to the distribution of the log likelihood ratio statistic is investigated by computer simulation in three situations of practical interest:tests of equality of exponential distributions, equality of normal distributions and equality of coefficients of variation of normal distributions.     

Order Statistics from the Generalized Exponential Distribution and Applications

With linear dispersion effects, the standard factorial designs are not optimal estimation of a mean model. A sequential two-stage experimental design procedure has been proposed that first estimates the variance structure, and then uses the variance estimates and the variance optimality criterion to develop a second stage design that efficiency estimates the mean model. This procedure has been compared to an equal replicate design analyzed by ordinary least squares, and found to be a superior procedure in many situations.

However with small first stage sample sizes the variance estiamtes are not reliable, and hence an alternative procedure could be more beneficial. For this reason a Bayesian modification to the two-stage procedure is proposed which will combine the first stage variance estiamtes with some prior variance information that will produce a more efficient procedure. This Bayesian procedure will be compared to the non-Bayesian twostage procedure and to the two one-stage alternative procedures listed above. Finally, a recommendation will be made as to which procedure is preferred in certain situations.     

Geometric Ergodicity and Moment Conditions for a Seasonal GARCH Model with Periodic Coefficients

A seasonal GARCH process with periodic coefficients is considered and conditions for periodic stationarity, geometric ergodicity, β-mixing property with exponential decay rate, and existence of higher-order moments are obtained.