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91.
James P. McDermott G. Jogesh Babu John C. Liechty Dennis K. J. Lin 《Statistics and Computing》2007,17(4):311-321
We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In
this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic.
We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve
that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed
for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation.
For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation
study to perform well and to have several distinct advantages over existing methods. 相似文献
92.
In this paper, we introduce a multivariate generalization of the population version of Gini's rank association coefficient,
giving a response to this open question posed in [4]. We also study some properties of this version, present the corresponding
results for the sample statistic, and provide several examples. 相似文献
93.
The Multiple-Try Metropolis is a recent extension of the Metropolis algorithm in which the next state of the chain is selected
among a set of proposals. We propose a modification of the Multiple-Try Metropolis algorithm which allows for the use of correlated
proposals, particularly antithetic and stratified proposals. The method is particularly useful for random walk Metropolis
in high dimensional spaces and can be used easily when the proposal distribution is Gaussian. We explore the use of quasi
Monte Carlo (QMC) methods to generate highly stratified samples. A series of examples is presented to evaluate the potential
of the method. 相似文献
94.
This paper considers the analysis of time to event data in the presence of collinearity between covariates. In linear and
logistic regression models, the ridge regression estimator has been applied as an alternative to the maximum likelihood estimator
in the presence of collinearity. The advantage of the ridge regression estimator over the usual maximum likelihood estimator
is that the former often has a smaller total mean square error and is thus more precise. In this paper, we generalized this
approach for addressing collinearity to the Cox proportional hazards model. Simulation studies were conducted to evaluate
the performance of the ridge regression estimator. Our approach was motivated by an occupational radiation study conducted
at Oak Ridge National Laboratory to evaluate health risks associated with occupational radiation exposure in which the exposure
tends to be correlated with possible confounders such as years of exposure and attained age. We applied the proposed methods
to this study to evaluate the association of radiation exposure with all-cause mortality. 相似文献
95.
This paper develops a new characterization of NBUC aging property, and investigates its preservation properties both under
monotonic anti-star-shaped transformations and under the non-homogeneous Poisson shock models. 相似文献
96.
The estimation of the means of the bivariate normal distribution, based on a sample obtained using a modification of the moving
extreme ranked set sampling technique (MERSS) is considered. The modification involves using a concomitant random variable.
Nonparametric-type methods as well as the maximum likelihood estimation are considered. The estimators obtained are compared
to their counterparts based on simple random sampling (SRS). It appears that the suggested estimators are more efficient.
Also, MERSS with concomitant variable is easier to use in practice than the usual ranked set sampling (RSS) with concomitant
variable. The issue of robustness of the procedure is addressed. Real trees data set is used for illustration. 相似文献
97.
Ricardo Maronna Matthias Fischer Jürgen Groß Andreas Karlsson 《Statistical Papers》2007,48(1):163-170
98.
This paper discusses the goodness-of-fit test for the proportional odds model for K-sample interval-censored failure time data, which frequently occur in, for example, periodic follow-up survival studies.
The proportional odds model has a feature that allows the ratio of two hazard functions to be monotonic and converge to one
and provides an important tool for the modeling of survival data. To test the model, a procedure is proposed, which is a generalization
of the method given in Dauxois and Kirmani [Dauxois JY, Kirmani SNUA (2003) Biometrika 90:913–922]. The asymptotic distribution
of the procedure is established and its properties are evaluated by simulation studies 相似文献
99.
Minimax estimation of a binomial probability under LINEX loss function is considered. It is shown that no equalizer estimator
is available in the statistical decision problem under consideration. It is pointed out that the problem can be solved by
determining the Bayes estimator with respect to a least favorable distribution having finite support. In this situation, the
optimal estimator and the least favorable distribution can be determined only by using numerical methods. Some properties
of the minimax estimators and the corresponding least favorable prior distributions are provided depending on the parameters
of the loss function. The properties presented are exploited in computing the minimax estimators and the least favorable distributions.
The results obtained can be applied to determine minimax estimators of a cumulative distribution function and minimax estimators
of a survival function. 相似文献
100.
Protfolio optimization is very sensitive to the forecats of returns and (co-)variances of the underlying assets. This paper
applies a Bayesian vector-autoregression of the asset universe to predict the returns. Further, the co-variance matrix is
forecasted by an Augmented GARCH estimation of the most volatile principle components of the return series. As an empirical
illustration, the daily stock returns of the German stocks index DAX have been used to calculate some well-known mean-variance
portfolios. Back-testing is used to evaluate the performance. The approach seems to be promising. 相似文献