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51.
Jason P. Fine David V. Glidden Kristine E. Lee 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2003,65(1):317-329
Summary. We propose a simple estimation procedure for a proportional hazards frailty regression model for clustered survival data in which the dependence is generated by a positive stable distribution. Inferences for the frailty parameter can be obtained by using output from Cox regression analyses. The computational burden is substantially less than that of the other approaches to estimation. The large sample behaviour of the estimator is studied and simulations show that the approximations are appropriate for use with realistic sample sizes. The methods are motivated by studies of familial associations in the natural history of diseases. Their practical utility is illustrated with sib pair data from Beaver Dam, Wisconsin. 相似文献
52.
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
53.
The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical
data are intrinsically stochastic and tend to be observed by means of discrete-time sampling systems, which are often limited
in their completeness. In this paper we explore how to make Bayesian inference for the kinetic rate constants of regulatory
networks, using the stochastic kinetic Lotka-Volterra system as a model. This simple model describes behaviour typical of
many biochemical networks which exhibit auto-regulatory behaviour. Various MCMC algorithms are described and their performance
evaluated in several data-poor scenarios. An algorithm based on an approximating process is shown to be particularly efficient. 相似文献
54.
Robin Willink 《Revue canadienne de statistique》2008,36(4):623-637
If the unknown mean of a univariate population is sufficiently close to the value of an initial guess then an appropriate shrinkage estimator has smaller average squared error than the sample mean. This principle has been known for some time, but it does not appear to have found extension to problems of interval estimation. The author presents valid two‐sided 95% and 99% “shrinkage” confidence intervals for the mean of a normal distribution. These intervals are narrower than the usual interval based on the Student distribution when the population mean lies in such an “effective interval.” A reduction of 20% in the mean width of the interval is possible when the population mean is sufficiently close to the value of the guess. The author also describes a modification to existing shrinkage point estimators of the general univariate mean that enables the effective interval to be enlarged. 相似文献
55.
Valentine Genon-Catalot Thierry Jeantheau Catherine Laredo 《Scandinavian Journal of Statistics》2003,30(2):297-316
ABSTRACT. This paper develops a new contrast process for parametric inference of general hidden Markov models, when the hidden chain has a non-compact state space. This contrast is based on the conditional likelihood approach, often used for ARCH-type models. We prove the strong consistency of the conditional likelihood estimators under appropriate conditions. The method is applied to the Kalman filter (for which this contrast and the exact likelihood lead to asymptotically equivalent estimators) and to the discretely observed stochastic volatility models. 相似文献
56.
A Sparse Implementation of the Average Information Algorithm for Factor Analytic and Reduced Rank Variance Models 总被引:1,自引:0,他引:1
Robin Thompson Brian Cullis Alison Smith Arthur Gilmour 《Australian & New Zealand Journal of Statistics》2003,45(4):445-459
Factor analytic variance models have been widely considered for the analysis of multivariate data particularly in the psychometrics area. Recently Smith, Cullis & Thompson (2001) have considered their use in the analysis of multi‐environment data arising from plant improvement programs. For these data, the size of the problem and the complexity of the variance models chosen to account for spatial heterogeneity within trials implies that standard algorithms for fitting factor analytic models can be computationally expensive. This paper presents a sparse implementation of the average information algorithm (Gilmour, Thompson & Cullis, 1995) for fitting factor analytic and reduced rank variance models. 相似文献
57.
JØRUND GÅSEMYR 《Scandinavian Journal of Statistics》2003,30(1):159-173
In this paper, we present a general formulation of an algorithm, the adaptive independent chain (AIC), that was introduced in a special context in Gåsemyr et al . [ Methodol. Comput. Appl. Probab. 3 (2001)]. The algorithm aims at producing samples from a specific target distribution Π, and is an adaptive, non-Markovian version of the Metropolis–Hastings independent chain. A certain parametric class of possible proposal distributions is fixed, and the parameters of the proposal distribution are updated periodically on the basis of the recent history of the chain, thereby obtaining proposals that get ever closer to Π. We show that under certain conditions, the algorithm produces an exact sample from Π in a finite number of iterations, and hence that it converges to Π. We also present another adaptive algorithm, the componentwise adaptive independent chain (CAIC), which may be an alternative in particular in high dimensions. The CAIC may be regarded as an adaptive approximation to the Gibbs sampler updating parametric approximations to the conditionals of Π. 相似文献
58.
Hee-Seok Oh Ta-Hsin Li 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2004,66(1):221-238
Summary. The paper considers the problem of estimating the entire temperature field for every location on the globe from scattered surface air temperatures observed by a network of weather-stations. Classical methods such as spherical harmonics and spherical smoothing splines are not efficient in representing data that have inherent multiscale structures. The paper presents an estimation method that can adapt to the multiscale characteristics of the data. The method is based on a spherical wavelet approach that has recently been developed for a multiscale representation and analysis of scattered data. Spatially adaptive estimators are obtained by coupling the spherical wavelets with different thresholding (selective reconstruction) techniques. These estimators are compared for their spatial adaptability and extrapolation performance by using the surface air temperature data. 相似文献
59.
合成了Eu(3-PYA)3·2H2O配合物,通过元素分析和化学分析确定了配合物的组成,测定了标题配合物的激光拉曼光谱.结果表明,标题配合物的羧基具有两种配位方式,分别为双齿和桥式.经与同构配合物Sm2(3-PYA)6·4H2O的晶体结构测定结果对照,知标题配合物中有一种Eu(Ⅲ)格位,中心离子的配位数为8 相似文献
60.
Modeling for Risk Assessment of Neurotoxic Effects 总被引:2,自引:0,他引:2
The regulation of noncancer toxicants, including neurotoxicants, has usually been based upon a reference dose (allowable daily intake). A reference dose is obtained by dividing a no-observed-effect level by uncertainty (safety) factors to account for intraspecies and interspecies sensitivities to a chemical. It is assumed that the risk at the reference dose is negligible, but no attempt generally is made to estimate the risk at the reference dose. A procedure is outlined that provides estimates of risk as a function of dose. The first step is to establish a mathematical relationship between a biological effect and the dose of a chemical. Knowledge of biological mechanisms and/or pharmacokinetics can assist in the choice of plausible mathematical models. The mathematical model provides estimates of average responses as a function of dose. Secondly, estimates of risk require selection of a distribution of individual responses about the average response given by the mathematical model. In the case of a normal or lognormal distribution, only an estimate of the standard deviation is needed. The third step is to define an adverse level for a response so that the probability (risk) of exceeding that level can be estimated as a function of dose. Because a firm response level often cannot be established at which adverse biological effects occur, it may be necessary to at least establish an abnormal response level that only a small proportion of individuals would exceed in an unexposed group. That is, if a normal range of responses can be established, then the probability (risk) of abnormal responses can be estimated. In order to illustrate this process, measures of the neurotransmitter serotonin and its metabolite 5-hydroxyindoleacetic acid in specific areas of the brain of rats and monkeys are analyzed after exposure to the neurotoxicant methylene-dioxymethamphetamine. These risk estimates are compared with risk estimates from the quantal approach in which animals are classified as either abnormal or not depending upon abnormal serotonin levels. 相似文献