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111.
In this article, we consider the problem of best linear unbiased estimation and best linear invariant estimation of the common scale parameter of several distributions using spacing of the pooled sample of all observations of individual samples. We derived conditions for the non negativity of the scale estimator obtained by the above methods. Further, we obtained necessary and sufficient conditions for the derived estimators to be constant multiples of the pooled sample range. 相似文献
112.
Suppose independent random samples are available from two normal populations with a common mean and unequal variances. Estimation of a quantile of the first population is considered with respect to the quadratic loss. Some new estimators for the quantile are proposed using some previously known estimators of a common mean. Inadmissibility results are proved for estimators which are equivariant under affine and location groups of transformations. Risk values of various estimators of a quantile are compared numerically using a detailed simulation study. 相似文献
113.
This article is concerned with the parameter estimation in linear regression model when it is suspected that the regression coefficients are the subspace of the equality restrictions. The objective of this article is to introduce the preliminary test almost unbiased Liu estimators (PTAULE) based on the Wald (W), the likelihood ratio (LR), and the Lagrangian multiplier (LM) tests and compare the proposed estimators in the sense of the quadratic bias and mean square error (MSE) criterion. 相似文献
114.
In this article, an efficient Bayesian meta-modeling approach is proposed for Gaussian stochastic process models in computer experiments. Different prior densities and particularly, a non informative hyper prior have been employed on the parameters involved in the correlation matrix. And the estimation of related parameters is obtained by the expectation-maximization algorithm. Compared with the recent work of Li and Sudjianto (2005), the proposed approach is not only of higher prediction accuracy but also of lower computational cost, due to the utilization of the non informative prior and the absence of tuning parameters. Experimental results demonstrate that our approach yields state-of-the-art performance. 相似文献
115.
N. Balakrishnan 《统计学通讯:理论与方法》2013,42(5):880-906
In this article, we establish several recurrence relations for the single and product moments of progressively Type-II right censored order statistics from a log-logistic distribution. The use of these relations in a systematic recursive manner would enable the computation of all the means, variances and covariances of progressively Type-II right censored order statistics from the log-logistic distribution for all sample sizes n, effective sample sizes m, and all progressive censoring schemes (R 1,…, R m ). The results established here generalize the corresponding results for the usual order statistics due to Balakrishnan and Malik (1987) and Balakrishnan et al. (1987). The moments so determined are then utilized to derive best linear unbiased estimators for the scale- and location-scale log-logistic distributions. A comparison of these estimates with the maximum likelihood estimates is made through Monte Carlo simulation. The best linear unbiased predictors of progressively censored failure times is then discussed briefly. Finally, a numerical example is presented to illustrate all the methods of inference developed here. 相似文献
116.
N. K. Sajeevkumar 《统计学通讯:理论与方法》2013,42(10):1780-1786
In this article, we consider the problem of best linear unbiased estimation and best linear invariant estimation of the scale parameter of a symmetric distribution using quasi-ranges is considered. We also prove a sufficient condition for the non negativity of the scale estimator obtained by the above method. Further, we obtain necessary and sufficient conditions for the derived estimators to be constant multiple of the sample range. 相似文献
117.
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119.
M.L. Tlku 《统计学通讯:理论与方法》2013,42(17):2043-2051
120.
Uniformly minimum variance unbiased estimators of several parameters of the multivariate lognormal distribution are expressed by using the hypergeometric functions of matrix argument. And the variances are given in special cases. 相似文献