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851.
Many of the usual criteria for optimal experimental design do not take into account the different scale of the variance of the parameters. Dette (1997) provided a standardization which leads to designs with similar efficiencies for all of the parameters. In this article, a new way of standardization through the coefficient of variation is given. This leads to designs useful when one of the parameters is expected to be very small. Thus, this criterion may be used if there is special interest in maximizing the power of some parameter tests. Locally standardized through the coefficient of variation A-optimal designs are computed for simple linear and quadratic regression. 相似文献
852.
In this article, it is shown how to compute, in an approximated way, probabilities of Type I error and Type II error of sequential Bayesian procedures for testing one-sided null hypotheses. First, some theoretical results are obtained, and then an algorithm is developed for applying these results. The prior predictive density plays a central role in this study. 相似文献
853.
In this article, we introduce a ridge estimator for the vector of parameters β in a semiparametric model when additional linear restrictions on the parameter vector are assumed to hold. We also obtain the semiparametric restricted ridge estimator for the parametric component in the semiparametric regression model. The ideas in this article are illustrated with a data set consisting of housing prices and through a comparison of the performances of the proposed and related estimators via a Monte Carlo simulation. 相似文献
854.
In this article, we give an asymptotic formula of order n ?1/2, where n is the sample size, for the skewness of the distributions of the maximum likelihood estimates of the pa-ra-meters in exponencial family nonlinear models. We generalize the result by Cordeiro and Cordeiro (2001). The formula is given in matrix notation and is very suitable for computer implementation and to obtain closed form expressions for a great variety of models. Some special cases and two applications are discussed. 相似文献
855.
In this article, Bayesian inference for the half-normal and half-t distributions using uninformative priors is considered. It is shown that exact Bayesian inference can be undertaken for the half-normal distribution without the need for Gibbs sampling. Simulation is then used to compare the sampling properties of Bayesian point and interval estimators with those of their maximum likelihood based counterparts. Inference for the half-t distribution based on the use of Gibbs sampling is outlined, and an approach to model comparison based on the use of Bayes factors is discussed. The fitting of the half-normal and half-t models is illustrated using real data on the body fat measurements of elite athletes. 相似文献
856.
In this article, several methods to make inferences about the parameters of a finite mixture of distributions in the context of centrally censored data with partial identification are revised. These methods are an adaptation of the work in Contreras-Cristán, Gutiérrez-Peña, and O'Reilly (2003) in the case of right censoring. The first method focuses on an asymptotic approximation to a suitably simplified likelihood using some latent quantities; the second method is based on the expectation-maximization (EM) algorithm. Both methods make explicit use of latent variables and provide computationally efficient procedures compared to non-Bayesian methods that deal directly with the full likelihood of the mixture appealing to its asymptotic approximation. The third method, from a Bayesian perspective, uses data augmentation to work with an uncensored sample. This last method is related to a recently proposed Bayesian method in Baker, Mengersen, and Davis (2005). Our proposal of the three adapted methods is shown to provide similar inferential answers, thus offering alternative analyses. 相似文献
857.
Maximal correlation has several desirable properties as a measure of dependence, including the fact that it vanishes if and only if the variables are independent. Except for a few special cases, it is hard to evaluate maximal correlation explicitly. We focus on two-dimensional contingency tables and discuss a procedure for estimating maximal correlation, which we use for constructing a test of independence. We compare the maximal correlation test with other tests of independence by Monte Carlo simulations. When the underlying continuous variables are dependent but uncorrelated, we point out some cases for which the new test is more powerful. 相似文献
858.
AbstractThis article presents a non-stochastic version of the Generalized Ridge Regression estimator that arises from a discussion of the properties of a Generalized Ridge Regression estimator whose shrinkage parameters are found to be close to their upper bounds. The resulting estimator takes the form of a shrinkage estimator that is superior to both the Ordinary Least Squares estimator and the James-Stein estimator under certain conditions. A numerical study is provided to investigate the range of signal to noise ratio under which the new estimator dominates the James-Stein estimator with respect to the prediction mean square error. 相似文献
859.
this article proposes a generalitation and improvement on the method of lenth (1989). the problem is solved by fixing outliers in highly contaminated samples. to do this a scale robust estimator is obtained and its performance is analyzed using computer simulations. the method is extremely simple to use and leads to the same results as the more complex one proposed by box and meyer(1986). 相似文献
860.
In this paper we compare the kernel density estimators proposed by Bhattacharyya et al. (1988) and Jones (1991) for length biased data, showing the asymptotic normality of the estimators. A method to construct a new estimator is proposed. Moreover, we extend these results to weighted data and we study an estimator for the weight function. 相似文献