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81.
Roger L. Berger 《Journal of statistical planning and inference》1980,4(4):391-402
Let (X1,…,Xk) be a multinomial vector with unknown cell probabilities (p1,?,pk). A subset of the cells is to be selected in a way so that the cell associated with the smallest cell probability is included in the selected subset with a preassigned probability, P1. Suppose the loss is measured by the size of the selected subset, S. Using linear programming techniques, selection rules can be constructed which are minimax with respect to S in the class of rules which satisfy the P1-condition. In some situations, the rule constructed by this method is the rule proposed by Nagel (1970). Similar techniques also work for selection in terms of the largest cell probability. 相似文献
82.
汤兆云 《江苏大学学报(社会科学版)》2006,8(6):42-44
师道,即“教人以道”,是教师责无旁贷之职责,义不容辞之要务。师道是一种责任。《李良玉历史研究与教育文选》一书凝聚着李良玉教授浓厚的“师道即师责”传统。在学业上,他耐心和细致地教诲每一个学生;在生活上,他如同对待子女般地关心他们。李良玉教授在用自己的行动诠释着新时期师道的真谛。 相似文献
83.
Raphael Godefroy Eduardo Perez‐Richet 《Econometrica : journal of the Econometric Society》2013,81(1):221-253
We study selection rules: voting procedures used by committees to choose whether to place an issue on their agenda. At the selection stage of the model, committee members are uncertain about their final preferences. They only have some private information about these preferences. We show that voters become more conservative when the selection rule itself becomes more conservative. The decision rule has the opposite effect. We compare these voting procedures to the designation of an agenda setter among the committee and to a utilitarian social planner with all the ex interim private information. 相似文献
84.
P. N. Gavriliadis 《统计学通讯:理论与方法》2013,42(5):671-681
How much information does a small number of moments carry about the unknown distribution function? Is it possible to explicitly obtain from these moments some useful information, e.g., about the support, the modality, the general shape, or the tails of a distribution, without going into a detailed numerical solution of the moment problem? In this paper a theoretical result of Johnson and Rogers is generalized to be valid for all moment problems and is exploited to demonstrate that a few moments are able to provide us with valuable information about the position of the mode of an unknown (unimodal) distribution. 相似文献
85.
Shuenn-Ren Cheng 《统计学通讯:理论与方法》2013,42(10):1553-1560
We observe X 1,…,X k , where X i has density f(x,θ i ) possessing monotone likelihood ratio. The best population corresponds to the largest θ i . We select the population corresponding to the largest X i . The goal is to attach the best possible p-value to the inference: the selected population has the uniquely largest θ i . Gutmann and Maymin (1987) considered the location parameter case and derived the supremum of the error probability by conditioning on S, the index of the largest X i . Using this conditioning approach, Kannan and Panchapakesan (2009) considered the problem for the gamma family. We consider here a unified approach to both the location and scale parameter cases, and obtain the supremum of the error probability without using conditioning. 相似文献
86.
The Akaike Information Criterion (AIC) is developed for selecting the variables of the nested error regression model where an unobservable random effect is present. Using the idea of decomposing the likelihood into two parts of “within” and “between” analysis of variance, we derive the AIC when the number of groups is large and the ratio of the variances of the random effects and the random errors is an unknown parameter. The proposed AIC is compared, using simulation, with Mallows' C p , Akaike's AIC, and Sugiura's exact AIC. Based on the rates of selecting the true model, it is shown that the proposed AIC performs better. 相似文献
87.
AbstractWe propose a unified approach for multilevel sample selection models using a generalized result on skew distributions arising from selection. If the underlying distributional assumption is normal, then the resulting density for the outcome is the continuous component of the sample selection density and has links with the closed skew-normal distribution (CSN). The CSN distribution provides a framework which simplifies the derivation of the conditional expectation of the observed data. This generalizes the Heckman’s two-step method to a multilevel sample selection model. Finite-sample performance of the maximum likelihood estimator of this model is studied through a Monte Carlo simulation. 相似文献
88.
Jerome Saracco 《统计学通讯:理论与方法》2013,42(10):2367-2393
We consider the semiparametric regression model introduced by Li (1991) and add to this model some linear constraints on the slope parameters. These constraints can be identifiability conditions or they may carry additional in¬formations on the slope parameters. Using a geometric argument, we develop a method to estimate the slope parameters. This link-free and distribution-free method splits in two steps: the first is a Sliced Inverse Regression (SIR); Canonical Analysis is used at the second step to transform the SIR estimates so that they satisfy the constraints. We establish yn-consistency and obtain the asymptotic distribution of the estimates. This estimation method is applied to the general sample selection model which is very useful in Econometrics. A simulation study shows that the method performs well in the example considered. 相似文献
89.
In many conventional scientific investigations with high or ultra-high dimensional feature spaces, the relevant features, though sparse, are large in number compared with classical statistical problems, and the magnitude of their effects tapers off. It is reasonable to model the number of relevant features as a diverging sequence when sample size increases. In this paper, we investigate the properties of the extended Bayes information criterion (EBIC) (Chen and Chen, 2008) for feature selection in linear regression models with diverging number of relevant features in high or ultra-high dimensional feature spaces. The selection consistency of the EBIC in this situation is established. The application of EBIC to feature selection is considered in a SCAD cum EBIC procedure. Simulation studies are conducted to demonstrate the performance of the SCAD cum EBIC procedure in finite sample cases. 相似文献
90.
This expository paper explains the philosophy of the indifference-zone approach and the subset-selection approach to ranking and selection procedures. It includes examples of operating characteristic curves and data applications for selection problems based on the binomial and normal distributions. A variety of different models and goals are provided with a list of references. 相似文献