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201.
Some real-world phenomena in geo-science, micro-economy, and turbulence, to name a few, can be effectively modeled by a fractional Brownian motion indexed by a Hurst parameter, a regularity level, and a scaling parameter σ2, an energy level. This article discusses estimation of a scaling parameter σ2 when a Hurst parameter is known. To estimate σ2, we propose three approaches based on maximum likelihood estimation, moment-matching, and concentration inequalities, respectively, and discuss the theoretical characteristics of the estimators and optimal-filtering guidelines. We also justify the improvement of the estimation of σ2 when a Hurst parameter is known. Using the three approaches and a parametric bootstrap methodology in a simulation study, we compare the confidence intervals of σ2 in terms of their lengths, coverage rates, and computational complexity and discuss empirical attributes of the tested approaches. We found that the approach based on maximum likelihood estimation was optimal in terms of efficiency and accuracy, but computationally expensive. The moment-matching approach was found to be not only comparably efficient and accurate but also computationally fast and robust to deviations from the fractional Brownian motion model. 相似文献
202.
Estimation of the mean of a multivariate normal distribution is considered. The components of the mean vector θ are assumed to be exchangeable; this is modelled in a hierarchical fashion with independent Cauchy distributions as the first-stage prior. The resulting generalized Bayes estimator is calculated and shown to be robust with respect to the presence of outlying means. Alternative estimators that have similar behaviour but are cheaper to compute are also derived. 相似文献
203.
Estimation of a smooth function is considered when observations on this function added with Gaussian errors are observed. The problem is formulated as a general linear model, and a hierarchical Bayesian approach is then used to study it. Credible bands are also developed for the function. Sensitivity analysis is conducted to determine the influence of the choice of priors on hyperparameters. Finally, the methodology is illustrated using real and simulated examples where it is compared with classical cubic splines. It is also shown that our approach provides a Bayesian solution to some problems in discrete time series. 相似文献
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206.
Ayça Çakmak Pehlivanlı 《Journal of applied statistics》2016,43(6):1140-1154
Classification of high-dimensional data set is a big challenge for statistical learning and data mining algorithms. To effectively apply classification methods to high-dimensional data sets, feature selection is an indispensable pre-processing step of learning process. In this study, we consider the problem of constructing an effective feature selection and classification scheme for data set which has a small number of sample size with a large number of features. A novel feature selection approach, named four-Staged Feature Selection, has been proposed to overcome high-dimensional data classification problem by selecting informative features. The proposed method first selects candidate features with number of filtering methods which are based on different metrics, and then it applies semi-wrapper, union and voting stages, respectively, to obtain final feature subsets. Several statistical learning and data mining methods have been carried out to verify the efficiency of the selected features. In order to test the adequacy of the proposed method, 10 different microarray data sets are employed due to their high number of features and small sample size. 相似文献
207.
Travassos Guilherme Fonseca Coelho Alexandre Bragança Arends-Kuenning Mary Paula 《Social indicators research》2022,163(2):925-951
Social Indicators Research - The growth of the elderly population and changes in household composition raise important questions regarding the level of well-being of the elderly in developing... 相似文献
208.
This study aimed to identify the trajectories of breadth of participation in organized activities during childhood and to examine the predictors of membership in these trajectories (child's individual and family characteristics measured in Kindergarten). A sample of 1038 children, recruited in Kindergarten, was assessed yearly between Kindergarten and grade 4. Semiparametric group‐based modeling brought out four trajectories: the no participation group (13.5 percent), the increasing group (26.4 percent), the decreasing group (14.1 percent), and the high group (46.1 percent). Prosociality predicted membership in the no participation group, as compared with the increasing group. Social withdrawal predicted membership in the no participation group, as compared with the high group. High family income and higher maternal education predicted membership in the increasing, decreasing, and high trajectory groups, as compared with the no participation group. Higher paternal education predicted membership in the high group, as compared with the increasing group. Overall, family variables had a greater impact than individual variables on the probability that the child would participate in a broader range of organized activities. 相似文献
209.
In this paper we introduce a wide class of integer-valued stochastic processes that allows to take into consideration, simultaneously, relevant characteristics observed in count data namely zero inflation, overdispersion and conditional heteroscedasticity. This class includes, in particular, the compound Poisson, the zero-inflated Poisson and the zero-inflated negative binomial INGARCH models, recently proposed in literature. The main probabilistic analysis of this class of processes is here developed. Precisely, first- and second-order stationarity conditions are derived, the autocorrelation function is deduced and the strict stationarity is established in a large subclass. We also analyse in a particular model the existence of higher-order moments and deduce the explicit form for the first four cumulants, as well as its skewness and kurtosis. 相似文献
210.
The finite distributed lag models include highly correlated variables as well as lagged and unlagged values of the same variables. Some problems are faced for this model when applying the ordinary least squares (OLS) method or econometric models such as Almon and Koyck models. The primary aim of this study is to compare performances of alternative estimators to the OLS estimator defined by combining the Almon estimator with some estimators using Almon (1965) data. A simulation study with different model parameters is performed and the estimators are compared according to the root mean square error (RMSE) and prediction mean square error (PMSE). 相似文献