江苏省中等职业学校专业设置调查及分析

专业是连接教育和经济的桥梁,专业设置是中等职业学校服务社会经济的重要载体。通过抽取江苏省50所重点中等职业学校来分析专业设置现状,对城乡中等职业学校设置的专业在工学结合、联合办学、对口升学与就业等方面进行了对比分析,发现江苏省中等职业学校专业设置还存在一定问题,提出了加强校企合作力度,积极创新人才培养模式和办学模式,加强城乡及区域间联合办学,加强骨干、特色专业建设,优化中等职业学校布局等建议。     

Closed‐form likelihoods for stochastic differential equation growth models

The authors derive closed‐form expressions for the full, profile, conditional and modified profile likelihood functions for a class of random growth parameter models they develop as well as Garcia's additive model. These expressions facilitate the determination of parameter estimates for both types of models. The profile, conditional and modified profile likelihood functions are maximized over few parameters to yield a complete set of parameter estimates. In the development of their random growth parameter models the authors specify the drift and diffusion coefficients of the growth parameter process in a natural way which gives interpretive meaning to these coefficients while yielding highly tractable models. They fit several of their random growth parameter models and Garcia's additive model to stock market data, and discuss the results. The Canadian Journal of Statistics 38: 474–487; 2010 © 2010 Statistical Society of Canada     

Confidence intervals for the mean of a population containing many zero values under unequal‐probability sampling

In many applications, a finite population contains a large proportion of zero values that make the population distribution severely skewed. An unequal‐probability sampling plan compounds the problem, and as a result the normal approximation to the distribution of various estimators has poor precision. The central‐limit‐theorem‐based confidence intervals for the population mean are hence unsatisfactory. Complex designs also make it hard to pin down useful likelihood functions, hence a direct likelihood approach is not an option. In this paper, we propose a pseudo‐likelihood approach. The proposed pseudo‐log‐likelihood function is an unbiased estimator of the log‐likelihood function when the entire population is sampled. Simulations have been carried out. When the inclusion probabilities are related to the unit values, the pseudo‐likelihood intervals are superior to existing methods in terms of the coverage probability, the balance of non‐coverage rates on the lower and upper sides, and the interval length. An application with a data set from the Canadian Labour Force Survey‐2000 also shows that the pseudo‐likelihood method performs more appropriately than other methods. The Canadian Journal of Statistics 38: 582–597; 2010 © 2010 Statistical Society of Canada     

Asymptotic normality of frequency polygons for random fields

The purpose of this paper is to investigate asymptotic normality of the frequency polygon estimator of a stationary mixing random field indexed by multidimensional lattice points space Z^N$Z^N$. Appropriate choices of the bandwidths are found.     

Some nonparametric precedence-type tests based on progressively censored samples and evaluation of power

In this paper, we consider the problem of testing the equality of two distributions when both samples are progressively Type-II censored. We discuss the following two statistics: one based on the Wilcoxon-type rank-sum precedence test, and the second based on the Kaplan–Meier estimator of the cumulative distribution function. The exact null distributions of these test statistics are derived and are then used to generate critical values and the corresponding exact levels of significance for different combinations of sample sizes and progressive censoring schemes. We also discuss their non-null distributions under Lehmann alternatives. A power study of the proposed tests is carried out under Lehmann alternatives as well as under location-shift alternatives through Monte Carlo simulations. Through this power study, it is shown that the Wilcoxon-type rank-sum precedence test performs the best.     

Mean and sensitivity estimation in optional randomized response models

Optional randomized response models were introduced by Gupta et al. (2002). These models are based on the basic premise that a question may be sensitive for one respondent but may not be sensitive for another. In an optional RRT (randomized response technique) model, a respondent is asked to provide a scrambled response only if the respondent considers the question sensitive. Otherwise, the respondent provides a truthful response. The researcher does not know which type of response is provided. The proportion of respondents who provide a scrambled response is known as the sensitivity level of the question. In this paper, we estimate simultaneously the mean and the sensitivity level of a quantitative-response sensitive question using a two stage optional RRT model. The estimators are unbiased and asymptotically normally distributed. We discuss the advantages and disadvantages of using additive and multiplicative scrambling.     

Data-dependent probability matching priors for highest posterior density and equal-tailed two-sided regions based on empirical-type likelihoods

We consider a very general class of empirical-type likelihoods which includes the usual empirical likelihood and all its major variants proposed in the literature. It is known that none of these likelihoods admits a data-free probability matching prior for the highest posterior density region. We develop necessary higher order asymptotics to show that at least for the usual empirical likelihood this difficulty can be resolved if data-dependent priors are entertained. A related problem concerning the equal-tailed two-sided posterior credible region is also investigated. A simulation study is seen to lend support to the theoretical results.     

基于G1法的判断矩阵的一致性分析

应用层次分析法(AHP)法的难点在于构造判断矩阵,构造判断矩阵的难点在于其一致性问题,本文用G1法分析造成AHP判断矩阵不一致的原因,指出了G1法与构造判断矩阵的本质区别,解决了层次分析法的应用难题.同时对一些文献基于构造判断矩阵得出的值得商榷的结论进行了讨论.     

More on the restricted ridge regression estimation

Several alternative methods for derivation of the restricted ridge regression estimator (RRRE) are provided. Theoretical comparison and relationship of RRRE with related methods for regression with the multicollinearity problem are described. We also find inter-connections among RRRE, ordinary ridge regression estimator (ORRE), restricted least squares estimator (RLSE), modified ridge regression estimator (MRRE) and restricted modified generalized ridge estimator (RMGRE). Finally, numerical comparison, in addition to theoretical derivation, is also conducted with a Monte Carlo simulation and a real data example.