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971.
C.C. Figueiredo H. Bolfarine M.C. Sandoval C.R.O.P. Lima 《Journal of applied statistics》2010,37(3):435-451
In this article, we present the EM-algorithm for performing maximum likelihood estimation of an asymmetric linear calibration model with the assumption of skew-normally distributed error. A simulation study is conducted for evaluating the performance of the calibration estimator with interpolation and extrapolation situations. As one application in a real data set, we fitted the model studied in a dimensional measurement method used for calculating the testicular volume through a caliper and its calibration by using ultrasonography as the standard method. By applying this methodology, we do not need to transform the variables to have symmetrical errors. Another interesting aspect of the approach is that the developed transformation to make the information matrix nonsingular, when the skewness parameter is near zero, leaves the parameter of interest unchanged. Model fitting is implemented and the best choice between the usual calibration model and the model proposed in this article was evaluated by developing the Akaike information criterion, Schwarz’s Bayesian information criterion and Hannan–Quinn criterion. 相似文献
972.
M. Burkschat 《Statistics》2013,47(5):383-392
We consider best linear equivariant estimation in a particular location-scale family based on several progressively type II censored samples. The censoring schemes that minimize the mean squared error matrix of the estimators with respect to the Löwner ordering are obtained. Uniqueness of the schemes, which minimize the smallest and the largest eigenvalue of the matrix is shown under some condition. 相似文献
973.
M.A. Ali 《统计学通讯:理论与方法》2013,42(8):2801-2811
In this article Bock's (1975) approach is used to fit a class of lower order polynomials to a higher order response function. For a wide class of conditions our fitted models offer greater protection, in some sense, against model inadequacies than the one fitted by Karson, Manson and Hader (1969). However, our approach is applicable to the situations where the assumption of normality about the distribution of the response variable is appropriate. 相似文献
974.
Razzaghi (1987) conjectured that a wrong choice of covariance matrix in a restricted linear model results in loss of efficiency. This conjecture was proved correct by Kabe and Gupta for a wrong choice of constant covariance matrix. The present paper demonstrates that this loss of efficiency persists even with an estimated covariance matrix, thereby resulting in inefficient estimation, prediction, and confidence intervals. 相似文献
975.
It is shown that a necessary and sufficient condition derived by Farebrother (1984)for a generalized ridge estimator to dominate the ordinary least-squares estimator with respect to the mean-square-error-matrix criterion in the linear regression model admits a similar interpretation as the well known criterion of Toro-Viz-carrondo and Wallace (1968)for the dominance of a restricted least-squares estimator over the ordinary least-squares estimator. Two other properties of the generalized ridge estimators, referring to the concept of admissibility, are also pointed out. 相似文献
976.
李伟勋 《湛江师范学院学报》1999,(2)
设A 是 m 阶整数矩阵,A 是由A 的全体方幂构成的集合.本文证明了:当 m > 9 时,如果A 的行列式| A| ≠0 ,而且A 的特征根不全为单位根,则A 上的Fermat 方程无解. 相似文献
977.
978.
Consider a k polynomial regression on a single real variable. If n uncorrelated observations are to be taken in a design with support on more than k+1 points, there is an approximate experiment, ν, with support on k+1 points and n observations such that both designs have the same information matrix for the model. A proof of this result is provided. A method to obtain the approximate design ν is given and illustrated by an example. The source of disagreement between Kiefer (1959) and De La Garza (1954) in the solution of this problem is clarified. 相似文献
979.
Bilgehan Güven 《Statistics》2013,47(6):545-557
We consider a linear regression model with an unbalanced 1-fold nested error structure, where group effect and error are from nonnormal universes. The limiting distribution of the F-statistic in this model is derived, as the sample size is large and group sizes take values from a finite set of distinct integers. The result is used to approximate the F-distribution quantile and to test the significance of the random effect variance component. Results are also applicable to the F-statistic in the one-way random-effects model. The effects of departure from normality on the F-statistic distribution are given. 相似文献
980.
Patrícia F. Paranaíba Gauss M. Cordeiro Marcelino A.R. de Pascoa 《Journal of Statistical Computation and Simulation》2013,83(11):2117-2143
For the first time, a five-parameter distribution, called the Kumaraswamy Burr XII (KwBXII) distribution, is defined and studied. The new distribution contains as special models some well-known distributions discussed in lifetime literature, such as the logistic, Weibull and Burr XII distributions, among several others. We obtain the complete moments, incomplete moments, generating and quantile functions, mean deviations, Bonferroni and Lorenz curves and reliability of the KwBXII distribution. We provide two representations for the moments of the order statistics. The method of maximum likelihood and a Bayesian procedure are adopted for estimating the model parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the KwBXII distribution. Three applications to real data sets demonstrate the usefulness of the proposed distribution and that it may attract wider applications in lifetime data analysis. 相似文献