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排序方式: 共有1176条查询结果,搜索用时 15 毫秒
1.
AbstractWeak convergence and moment convergence issues are investigated for the New Better than Average Failure Rate (NBAFR) family (introduced by Loh (1984)). We explore the validity of these results in the context of a more general ageing class that we introduce. We prove some new properties of this class and derive its interrelationships with other non-monotonic ageing families. Reliability and moment bounds are obtained and an interesting characterization of exponentiality is proved. Special cases of our results lead to new theorems for the NBAFR class. Finally weak convergence and related issues are established for this class. 相似文献
2.
陈忠 《长江大学学报(社会科学版)》2003,(2)
提出了一种求解等式约束优化问题的异步并行拟牛顿方法 .若假设目标函数 f和约束函数h至少三次连续可微 ,且△h(x)对任意x∈Rn 均为满秩矩阵 ,证明了所提出的异步并行算法是 q—超线性收敛的 . 相似文献
3.
Jianqing Fan 《Revue canadienne de statistique》1992,20(2):155-169
Nonparametric deconvolution problems require one to recover an unknown density when the data are contaminated with errors. Optimal global rates of convergence are found under the weighted Lp-loss (1 ≤ p ≤ ∞). It appears that the optimal rates of convergence are extremely low for supersmooth error distributions. To resolve this difficulty, we examine how high the noise level can be for deconvolution to be feasible, and for the deconvolution estimate to be as good as the ordinary density estimate. It is shown that if the noise level is not too high, nonparametric Gaussian deconvolution can still be practical. Several simulation studies are also presented. 相似文献
4.
CATIA SCRICCIOLO 《Scandinavian Journal of Statistics》2007,34(3):626-642
Abstract. We consider the problem of estimating a compactly supported density taking a Bayesian nonparametric approach. We define a Dirichlet mixture prior that, while selecting piecewise constant densities, has full support on the Hellinger metric space of all commonly dominated probability measures on a known bounded interval. We derive pointwise rates of convergence for the posterior expected density by studying the speed at which the posterior mass accumulates on shrinking Hellinger neighbourhoods of the sampling density. If the data are sampled from a strictly positive, α -Hölderian density, with α ∈ ( 0,1] , then the optimal convergence rate n− α / (2 α +1) is obtained up to a logarithmic factor. Smoothing histograms by polygons, a continuous piecewise linear estimator is obtained that for twice continuously differentiable, strictly positive densities satisfying boundary conditions attains a rate comparable up to a logarithmic factor to the convergence rate n −4/5 for integrated mean squared error of kernel type density estimators. 相似文献
5.
Song Xi Chen Wolfgang Härdle Ming Li 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2003,65(3):663-678
Summary. Standard goodness-of-fit tests for a parametric regression model against a series of nonparametric alternatives are based on residuals arising from a fitted model. When a parametric regression model is compared with a nonparametric model, goodness-of-fit testing can be naturally approached by evaluating the likelihood of the parametric model within a nonparametric framework. We employ the empirical likelihood for an α -mixing process to formulate a test statistic that measures the goodness of fit of a parametric regression model. The technique is based on a comparison with kernel smoothing estimators. The empirical likelihood formulation of the test has two attractive features. One is its automatic consideration of the variation that is associated with the nonparametric fit due to empirical likelihood's ability to Studentize internally. The other is that the asymptotic distribution of the test statistic is free of unknown parameters, avoiding plug-in estimation. We apply the test to a discretized diffusion model which has recently been considered in financial market analysis. 相似文献
6.
黄廷祝 《电子科技大学学报(社会科学版)》1996,(6)
研究大型线性方程组迭代解法中分块JACOBI迭代阵的收敛性。采用块矩阵分析方法和谱半径降维估计法得到块Jacobi迭代阵收敛的实用充分条件。 相似文献
7.
经济收敛理论与检验方法研究综述 总被引:4,自引:0,他引:4
在大量文献研究的基础上,对收敛问题的产生及收敛概念的发展作了全面概括,并对绝对收敛、条件收敛、俱乐部收敛和σ收敛作了深入辨析,对各种识别方法作了全面归纳。归纳了对世界大多数国家和地区数据所作识别的结果。还从收敛理论与传统理论的冲突与协调方面作了深入分析。最后对近年收敛研究的深化与扩展研究的趋势作了概括。 相似文献
8.
9.
M. Jamshidian & R. I. Jennrich 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2000,62(2):257-270
The EM algorithm is a popular method for computing maximum likelihood estimates. One of its drawbacks is that it does not produce standard errors as a by-product. We consider obtaining standard errors by numerical differentiation. Two approaches are considered. The first differentiates the Fisher score vector to yield the Hessian of the log-likelihood. The second differentiates the EM operator and uses an identity that relates its derivative to the Hessian of the log-likelihood. The well-known SEM algorithm uses the second approach. We consider three additional algorithms: one that uses the first approach and two that use the second. We evaluate the complexity and precision of these three and the SEM in algorithm seven examples. The first is a single-parameter example used to give insight. The others are three examples in each of two areas of EM application: Poisson mixture models and the estimation of covariance from incomplete data. The examples show that there are algorithms that are much simpler and more accurate than the SEM algorithm. Hopefully their simplicity will increase the availability of standard error estimates in EM applications. It is shown that, as previously conjectured, a symmetry diagnostic can accurately estimate errors arising from numerical differentiation. Some issues related to the speed of the EM algorithm and algorithms that differentiate the EM operator are identified. 相似文献
10.
The recursive least squares technique is often extended with exponential forgetting as a tool for parameter estimation in time-varying systems. The distribution of the resulting parameter estimates is, however, unknown when the forgetting factor is less than one. In this paper an approximative expression for bias of the recursively obtained parameter estimates in a time-invariant AR( na ) process with arbitrary noise is given, showing that the bias is non-zero and giving bounds on the approximation errors. Simulations confirm the approximation expressions. 相似文献