新常态下货币供给对工业经济的非对称冲击——兼论冲击路径的情景设计与分析

货币政策冲击对工业产出和价格的非对称影响，是新常态下把握好货币供给政策的方向、力度和节奏的重要参考依据，有助于提升货币供给政策的针对性、灵活性和前瞻性。局部投影方法在不同区制下，计算工业产出和价格对货币供给冲击的脉冲响应结果表明：货币供给冲击对工业产出的影响具有不确定性，且总体上表现为中性特征；而货币供给冲击对工业价格的影响不仅在不同区制下，而且在新常态前后均表现出显著的差异性和非对称性，总体来说是短期有效，长期中性的。情景设计的分析结果显示新常态下采用增加货币供给的政策来刺激工业经济是不可取的，其作用效果可能出现工业产出停滞不前，工业价格急剧飙升的工业滞胀。因此，需要从工业产业升级，工业技术创新等工业供给侧寻求工业经济新的增长点和动力机制。     

Quadratic estimators of covariance components in a multivariate mixed linear model

It is known that the Henderson Method III (Biometrics 9:226–252, 1953) is of special interest for the mixed linear models because the estimators of the variance components are unaffected by the parameters of the fixed factor (or factors). This article deals with generalizations and minor extensions of the results obtained for the univariate linear models. A MANOVA mixed model is presented in a convenient form and the covariance components estimators are given on finite dimensional linear spaces. The results use both the usual parametric representations and the coordinate-free approach of Kruskal (Ann Math Statist 39:70–75, 1968) and Eaton (Ann Math Statist 41:528–538, 1970). The normal equations are generalized and it is given a necessary and sufficient condition for the existence of quadratic unbiased estimators for covariance components in the considered model.     

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.     

洋桔梗叶盘高频率不定芽诱导的初步研究

采用正交设计法研究了细胞分裂素ZT,生长素NAA,培养基pH值和光照强度对洋桔梗叶盘不定芽诱导的影响.结果表明,实验的4个因子对洋桔梗叶盘不定芽都具有极显著的诱导作用,最佳培养基和培养条件为:MS ZT 0.5 mg/L NAA 0.01 mg/L,培养基pH值为6.3,光照强度为3000 lx.该处理中每叶盘再生不定芽数平均达9.41个.     

指示语映射现象探析

以说话人自我为中心是指示语的一个重要属性,也是交际过程中各方都基本认同的参照准则。但有的时候说话人为了达到某种特殊的效果,如语用移情效果,会有意选择违背以说话人自我为中心这条准则,把指示中心转移到听话人或其他听众身上,从而发生了指示语映射现象。对这种语言现象的深入了解和分析,有助于正确理解和使用指示词语,从而更深刻地认识指示这一现象的语用性质。     

Model diagnostics for smoothing spline ANOVA models

The author proposes some simple diagnostics for assessing the necessity of selected terms in smoothing spline ANOVA models. The elimination of practically insignificant terms generally enhances the interpretability of the estimates and sometimes may also have inferential implications. The diagnostics are derived from Kullback‐Leibler geometry and are illustrated in the settings of regression, probability density estimation, and hazard rate estimation.     

频率与投射在二语习得中的互补性

以频率为中心的二语习得理论认为,输入频率是影响第二语言习得顺序的重要因素,并对语言结构的能产性起着决定作用。投射假设则认为,语言习得并不完全以语言输入为基础,学习者对某个语言参数的习得往往蕴含着对另外一个相关参数的习得。频率和投射从不同的侧面揭示了第二语言习得的特点,在教学中恰当地利用这种互补有利于促进语言习得的进程,提高教学效率。     

随机变量投影的一种应用

利用随机变量的投影关系,定义了偏方差矩阵,从而导出了逆方差阵元素的一种形式在随机变量是正态的条件,它为判别条件独立性有方便的操作办法。     

Approximation of density functions by orthogonal series with grouped data

Summary Letg(x) andf(x) be continuous density function on (a, b) and let {ϕ_j} be a complete orthonormal sequence of functions onL ₂(g), which is the set of squared integrable functions weighted byg on (a, b). Suppose that over (a, b). Given a grouped sample of sizen fromf(x), the paper investigates the asymptotic properties of the restricted maximum likelihood estimator of density, obtained by setting all but the firstm of the ϑ_j’s equal to0. Practical suggestions are given for performing estimation via the use of Fourier and Legendre polynomial series. Research partially supported by: CNR grant, n. 93. 00837. CT10.     

Implementing partial least squares

Partial least squares (PLS) regression has been proposed as an alternative regression technique to more traditional approaches such as principal components regression and ridge regression. A number of algorithms have appeared in the literature which have been shown to be equivalent. Someone wishing to implement PLS regression in a programming language or within a statistical package must choose which algorithm to use. We investigate the implementation of univariate PLS algorithms within FORTRAN and the Matlab (1993) and Splus (1992) environments, comparing theoretical measures of execution speed based on flop counts with their observed execution times. We also comment on the ease with which the algorithms may be implemented in the different environments. Finally, we investigate the merits of using the orthogonal invariance of PLS regression to improve the algorithms.