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511.
李发昇 《西安电子科技大学学报(社会科学版)》2011,21(1):56-63
政府支出对经济增长产生重要影响。本文对政府支出与经济增长关系重要但不确定的原因进行了深入分析,指出将政府支出中的投入要素和影响因素分开,分别研究其与经济增长的关系,实证分析验证了影响因素的作用特点,这些研究成果对指导我国新时期政策制定具有重要的现实意义。 相似文献
512.
针对分布式实时嵌入式系统DRES,设计了一种提供自适应服务质量(QoS)保证的构件模型QuOCCM,以形式化方法描述构件,并推导构件各实体之间的自适应过程。QuOCCM由三部分组成,Client、Qoskets和Server,分别以CCM(CORBA Component Model)构件技术实现。Client与应用或功能构件交互,获取当前QoS需求,并触发自适应机制;Qoskets通过对QoS保证框架QuO进行改进,以构件技术实现QoS自适应调整策略;Server提供自适应调整之后的QoS保证机制。研究结果表明,该方法不仅保证了DRES中当前应用环境的QoS自适应需求,而且QoS保证与具体功能应用分离也降低了系统开发的复杂性。形式化方法研究为构件实体间的交互提供了保证。 相似文献
513.
R. C. Gupta 《Statistics》2013,47(1):43-52
The purpose of this article is to study the bivariate distributions with second kind of beta conditionals, presented by Castillo and Sarabia, from a reliability point of view. The reliability functions, viz the survival function, the failure rate and mean residual life function, are derived and their monotonicity is discussed for the univariate model as well as the conditional model. Finally, Clayton’s association measure is obtained in terms of the hazard gradient and its value, in the case of our model, is derived. 相似文献
514.
M. Revan Özkale 《Statistics》2013,47(6):541-551
In this article, we introduce restricted principal components regression (RPCR) estimator by combining the approaches followed in obtaining the restricted least squares estimator and the principal components regression estimator. The performance of the RPCR estimator with respect to the matrix and the generalized mean square error are examined. We also suggest a testing procedure for linear restrictions in principal components regression by using singly and doubly non-central F distribution. 相似文献
515.
Baolin Wu 《Journal of applied statistics》2013,40(2):358-367
Currently, extreme large-scale genetic data present significant challenges for cluster analysis. Most of the existing clustering methods are typically built on the Euclidean distance and geared toward analyzing continuous response. They work well for clustering, e.g. microarray gene expression data, but often perform poorly for clustering, e.g. large-scale single nucleotide polymorphism (SNP) data. In this paper, we study the penalized latent class model for clustering extremely large-scale discrete data. The penalized latent class model takes into account the discrete nature of the response using appropriate generalized linear models and adopts the lasso penalized likelihood approach for simultaneous model estimation and selection of important covariates. We develop very efficient numerical algorithms for model estimation based on the iterative coordinate descent approach and further develop the expectation–maximization algorithm to incorporate and model missing values. We use simulation studies and applications to the international HapMap SNP data to illustrate the competitive performance of the penalized latent class model. 相似文献
516.
ABSTRACT Confidence intervals for the intraclass correlation coefficient (ρ) are used to determine the optimal allocation of experimental material in one-way random effects models. Designs that produce narrow intervals are preferred since they provide greater precision to estimate ρ. Assuming the total cost and the relative cost of the two stages of sampling are fixed, the authors investigate the number of classes and the number of individuals per class required to minimize the expected length of confidence intervals. We obtain results using asymptotic theory and compare these results to those obtained using exact calculations. The best design depends on the unknown value of ρ. Minimizing the maximum expected length of confidence intervals guards against worst-case scenarios. A good overall recommendation based on asymptotic results is to choose a design having classes of size 2 + √4 + 3r, where r is the relative cost of sampling at the class-level compared to the individual-level. If r = 0, then the overall cost is the sample size and the recommendation reduces to a design having classes of size 4. 相似文献
517.
Jean-Michel Marin 《统计学通讯:理论与方法》2013,42(12):2273-2288
The linear Toeplitz covariance structure model of order one is considered. We give some elegant explicit expressions of the Locally Minimum Variance Quadratic Unbiased Estimators of its covariance parameters. We deduce from a Monte Carlo method some properties of their Gaussian maximum likelihood estimators. Finally, for small sample sizes, these two types of estimators are compared with the intuitive empirical estimators and it is shown that the empirical biased estimators should be used. 相似文献
518.
This article considers a generalization of the functional linear regression in which an additional real variable influences smoothly the functional coefficient. We thus define a varying-coefficient regression model for functional data. We propose two estimators based, respectively, on conditional functional principal regression and on local penalized regression splines and prove their pointwise consistency. We check, with the prediction one day ahead of ozone concentration in the city of Toulouse, the ability of such nonlinear functional approaches to produce competitive estimations. 相似文献
519.
Dário Ferreira Sandra S. Ferreira Célia Nunes Miguel Fonseca João T. Mexia 《统计学通讯:理论与方法》2013,42(22):5445-5466
AbstractWe use chi-squared and related pivot variables to induce probability measures for model parameters, obtaining some results that will be useful on the induced densities. As illustration we considered mixed models with balanced cross nesting and used the algebraic structure to derive confidence intervals for the variance components. A numerical application is presented. 相似文献
520.
Sample size determination for quality control process using a multiple components tolerance interval
Feng-Shou Ko 《统计学通讯:理论与方法》2013,42(12):3668-3674
ABSTRACTIn the past, a tolerance interval was used for the statistical quality control process on raw materials and/or the final product. In the traditional concept of the tolerance interval, the variance from the measurements is a single component. However, we can find examples about several components that could vary in their measurements, so an approximate method must be found to modify the traditional tolerance interval. Now we employ a tolerance interval considering multiple components in the variance from the measurements to deal with quality control process. In our paper, the proposed method is used to solve the sample size determination for a two-sided tolerance interval approach considering multiple components on the variance of measurements. 相似文献