全文获取类型
收费全文 | 3836篇 |
免费 | 84篇 |
国内免费 | 15篇 |
专业分类
管理学 | 383篇 |
民族学 | 6篇 |
人口学 | 69篇 |
丛书文集 | 54篇 |
理论方法论 | 95篇 |
综合类 | 353篇 |
社会学 | 250篇 |
统计学 | 2725篇 |
出版年
2024年 | 1篇 |
2023年 | 27篇 |
2022年 | 32篇 |
2021年 | 38篇 |
2020年 | 63篇 |
2019年 | 110篇 |
2018年 | 159篇 |
2017年 | 242篇 |
2016年 | 116篇 |
2015年 | 119篇 |
2014年 | 122篇 |
2013年 | 886篇 |
2012年 | 281篇 |
2011年 | 141篇 |
2010年 | 126篇 |
2009年 | 158篇 |
2008年 | 152篇 |
2007年 | 146篇 |
2006年 | 121篇 |
2005年 | 135篇 |
2004年 | 111篇 |
2003年 | 92篇 |
2002年 | 71篇 |
2001年 | 75篇 |
2000年 | 70篇 |
1999年 | 56篇 |
1998年 | 52篇 |
1997年 | 38篇 |
1996年 | 19篇 |
1995年 | 16篇 |
1994年 | 27篇 |
1993年 | 18篇 |
1992年 | 19篇 |
1991年 | 13篇 |
1990年 | 11篇 |
1989年 | 8篇 |
1988年 | 12篇 |
1987年 | 7篇 |
1986年 | 4篇 |
1985年 | 8篇 |
1984年 | 6篇 |
1983年 | 9篇 |
1982年 | 9篇 |
1981年 | 1篇 |
1980年 | 2篇 |
1979年 | 2篇 |
1978年 | 2篇 |
1977年 | 1篇 |
1976年 | 1篇 |
排序方式: 共有3935条查询结果,搜索用时 15 毫秒
971.
Huazhen Lin Baoying Yang Ling Zhou Paul S. F. Yip Ying‐Yeh Chen Hua Liang 《Revue canadienne de statistique》2019,47(3):487-519
We propose a varying‐coefficient autoregressive model that contains additive models, varying‐ coefficient models, partially linear models and low‐dimensional interaction models as special cases. A global kernel backfitting method is proposed for the estimation and inference of parameters and unknown functions in this model. Key large‐sample results are established, including estimation consistency, asymptotic normality and the generalized likelihood ratio test for parameters and non‐parametric functions. The proposed methodology is examined by simulation studies and applied to examine the relationship between suicide news reports in the three leading newspapers and the daily number of suicides in Taiwan. The relationship between the media reporting and suicide incidence has been established and explored. The Canadian Journal of Statistics 47: 487–519; 2019 © 2019 Statistical Society of Canada 相似文献
972.
Tian Gu Jeremy M. G. Taylor Wenting Cheng Bhramar Mukherjee 《Revue canadienne de statistique》2019,47(4):580-603
We consider the situation where there is a known regression model that can be used to predict an outcome, Y, from a set of predictor variables X . A new variable B is expected to enhance the prediction of Y. A dataset of size n containing Y, X and B is available, and the challenge is to build an improved model for Y| X ,B that uses both the available individual level data and some summary information obtained from the known model for Y| X . We propose a synthetic data approach, which consists of creating m additional synthetic data observations, and then analyzing the combined dataset of size n + m to estimate the parameters of the Y| X ,B model. This combined dataset of size n + m now has missing values of B for m of the observations, and is analyzed using methods that can handle missing data (e.g., multiple imputation). We present simulation studies and illustrate the method using data from the Prostate Cancer Prevention Trial. Though the synthetic data method is applicable to a general regression context, to provide some justification, we show in two special cases that the asymptotic variances of the parameter estimates in the Y| X ,B model are identical to those from an alternative constrained maximum likelihood estimation approach. This correspondence in special cases and the method's broad applicability makes it appealing for use across diverse scenarios. The Canadian Journal of Statistics 47: 580–603; 2019 © 2019 Statistical Society of Canada 相似文献
973.
B. Béranger T. Duong S. E. Perkins-Kirkpatrick S. A. Sisson 《Journal of nonparametric statistics》2019,31(1):144-174
It is often critical to accurately model the upper tail behaviour of a random process. Nonparametric density estimation methods are commonly implemented as exploratory data analysis techniques for this purpose and can avoid model specification biases implied by using parametric estimators. In particular, kernel-based estimators place minimal assumptions on the data, and provide improved visualisation over scatterplots and histograms. However kernel density estimators can perform poorly when estimating tail behaviour above a threshold, and can over-emphasise bumps in the density for heavy tailed data. We develop a transformation kernel density estimator which is able to handle heavy tailed and bounded data, and is robust to threshold choice. We derive closed form expressions for its asymptotic bias and variance, which demonstrate its good performance in the tail region. Finite sample performance is illustrated in numerical studies, and in an expanded analysis of the performance of global climate models. 相似文献
974.
Surveillance data provide a vital source of information for assessing the spread of a health problem or disease of interest and for planning for future health-care needs. However, the use of surveillance data requires proper adjustments of the reported caseload due to underreporting caused by reporting delays within a limited observation period. Although methods are available to address this classic statistical problem, they are largely focused on inference for the reporting delay distribution, with inference about caseload of disease incidence based on estimates for the delay distribution. This approach limits the complexity of models for disease incidence to provide reliable estimates and projections of incidence. Also, many of the available methods lack robustness since they require parametric distribution assumptions. We propose a new approach to overcome such limitations by allowing for separate models for the incidence and the reporting delay in a distribution-free fashion, but with joint inference for both modeling components, based on functional response models. In addition, we discuss inference about projections of future disease incidence to help identify significant shifts in temporal trends modeled based on the observed data. This latter issue on detecting ‘change points’ is not sufficiently addressed in the literature, despite the fact that such warning signs of potential outbreak are critically important for prevention purposes. We illustrate the approach with both simulated and real data, with the latter involving data for suicide attempts from the Veteran Healthcare Administration. 相似文献
975.
Lei Shi Md. Mostafizur Rahman Wen Gan Jianhua Zhao 《Journal of applied statistics》2015,42(2):428-444
Detection of outliers or influential observations is an important work in statistical modeling, especially for the correlated time series data. In this paper we propose a new procedure to detect patch of influential observations in the generalized autoregressive conditional heteroskedasticity (GARCH) model. Firstly we compare the performance of innovative perturbation scheme, additive perturbation scheme and data perturbation scheme in local influence analysis. We find that the innovative perturbation scheme give better result than other two schemes although this perturbation scheme may suffer from masking effects. Then we use the stepwise local influence method under innovative perturbation scheme to detect patch of influential observations and uncover the masking effects. The simulated studies show that the new technique can successfully detect a patch of influential observations or outliers under innovative perturbation scheme. The analysis based on simulation studies and two real data sets show that the stepwise local influence method under innovative perturbation scheme is efficient for detecting multiple influential observations and dealing with masking effects in the GARCH model. 相似文献
976.
977.
Ariel Alonso Elasma Milanzi Geert Molenberghs Christophe Buyck Luc Bijnens 《Pharmaceutical statistics》2015,14(2):129-138
Expert opinion plays an important role when selecting promising clusters of chemical compounds in the drug discovery process. Indeed, experts can qualitatively assess the potential of each cluster, and with appropriate statistical methods, these qualitative assessments can be quantified into a success probability for each of them. However, one crucial element often overlooked is the procedure by which the clusters are assigned to/selected by the experts for evaluation. In the present work, the impact such a procedure may have on the statistical analysis and the entire evaluation process is studied. It has been shown that some implementations of the selection procedure may seriously compromise the validity of the evaluation even when the rating and selection processes are independent. Consequently, the fully random allocation of the clusters to the experts is strongly advocated. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
978.
E. Bahrami Samani 《Journal of applied statistics》2014,41(12):2761-2776
In this paper, we study the indentifiability of a latent random effect model for the mixed correlated continuous and ordinal longitudinal responses. We derive conditions for the identifiability of the covariance parameters of the responses. Also, we proposed sensitivity analysis to investigate the perturbation from the non-identifiability of the covariance parameters, it is shown how one can use some elements of covariance structure. These elements associate conditions for identifiability of the covariance parameters of the responses. Influence of small perturbation of these elements on maximal normal curvature is also studied. The model is illustrated using medical data. 相似文献
979.
《Journal of Statistical Computation and Simulation》2012,82(10):2059-2071
Alternating logistic regressions (ALRs) seem to offer some of the advantages of marginal models estimated via generalized estimating equations (GEE) and generalized linear mixed models (GLMMs). Via simulation study we compared ALRs to marginal models estimated via GEE and subject-specific models estimated via GLMMs, with a focus on estimation of the correlation structure in three-level data sets (e.g. students in classes in schools). Data set size and structure, and amount of correlation in the data sets were varied. For simple correlation structures, ALRs performed well. For three-level correlation structures, all approaches, but especially ALRs, had difficulty assigning the correlation to the correct level, though sample sizes used were small. In addition, ALRs and GEEs had trouble attaching correct inference to the mean effects, though this improved as overall sample size improved. ALRs are a valuable addition to the data analyst's toolkit, though care should be taken when modelling data with three-level structures. 相似文献
980.
《Journal of Statistical Computation and Simulation》2012,82(15):3127-3133
ABSTRACTAs a compromise between parametric regression and non-parametric regression models, partially linear models are frequently used in statistical modelling. This paper is concerned with the estimation of partially linear regression model in the presence of multicollinearity. Based on the profile least-squares approach, we propose a novel principal components regression (PCR) estimator for the parametric component. When some additional linear restrictions on the parametric component are available, we construct a corresponding restricted PCR estimator. Some simulations are conducted to examine the performance of our proposed estimators and the results are satisfactory. Finally, a real data example is analysed. 相似文献