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131.
Liu Zhibin 《统计学通讯:理论与方法》2013,42(20):5873-5883
ABSTRACTThe neural network prediction method gets good historical matching between prediction indices and influence factor indices, while the differential simulation prediction method can reflect the changing trend of prediction indices; considering these new traits, a new multi-factor prediction method is proposed to organically combine these two prediction methods. At first, the input–output relation between water flooding efficiency in ultra-high water cut stage and their influence factors is viewed as a time varying system, then the BP neural network is introduced in parameter identification of differential simulation to obtain a new multi-factor prediction method of functional simulation based on the time varying system. This new prediction model has got good self-adaptability since its parameters change by time. Moreover, it has better results in the mid-long-term water flooding efficiency prediction because the non convergence problem appeared in the coupling process can be overcome in the training process of the neural network by variable learning rates. In the end, practical output prediction cases in two different oilfield blocks in China are given. The computational results show that the prediction results obtained using the new multi-factor prediction method are in good agreement with the reality, even much better than the results obtained by other prediction methods. 相似文献
132.
The problem of classifying a covariance stationary normal time series is considered. Under certain regularity conditions, a compact form of the linear discriminant function in the sense of maximizing the Bhattacharyya distance is obtained. 相似文献
133.
This article presents a model-based signal extraction seasonal adjustment procedure to extract estimates of the independent unobserved seasonal and nonseasonal components from an observed time series. The decomposition yields a one-sided filter that is optimal for adjusting the most recent observation under the assumption of using only the past observed series. Some advantages of this procedure are that no forecasts are required for implementation and there are no problems of revision of estimates or questions of concurrent adjustment. Comparisons are made with existing procedures using two-sided filters. 相似文献
134.
This article reviews Bayesian inference from the perspective that the designated model is misspecified. This misspecification has implications in interpretation of objects, such as the prior distribution, which has been the cause of recent questioning of the appropriateness of Bayesian inference in this scenario. The main focus of this article is to establish the suitability of applying the Bayes update to a misspecified model, and relies on representation theorems for sequences of symmetric distributions; the identification of parameter values of interest; and the construction of sequences of distributions which act as the guesses as to where the next observation is coming from. A conclusion is that a clear identification of the fundamental starting point for the Bayesian is described. 相似文献
135.
Shaowen Wu 《统计学通讯:模拟与计算》2013,42(8):1590-1604
We reinvestigate the empirical problem of lag length selection in unit root tests when using the augmented Dickey–Fuller test based on GLS-detrending. We extend the Ng and Perron (1995) work on this issue by applying the finite sample critical values calculated using the formulae proposed by Cheung and Lai (1995). Unlike Ng and Perron (2001) we find through simulation studies that the method of selecting lag length using the sequential t-test in the ADF regression of GLS-detrended series performs the best in most cases. 相似文献
136.
The proposed test detects deviations from randomness, without a priori distributional assumption, when observations are not independent and identically distributed (i.i.d.), which is suitable for our motivating stock market index data. Departures from i.i.d. are tested by subdividing data into subintervals and then using a conditional probability measure within intervals as a binomial test. This nonparametric test is designed to detect deviations of neighboring observations from randomness when the dataset consists of time series observations. Simulation results and a comparison with Lo and MacKinlay's (1988) variance ratio test showed that our proposed test is a competitive alternative. 相似文献
137.
In our previous work, we developed a new distance function based on a derivative and showed that our algorithm is effective. In contrast to well-known measures from the literature, our approach considers the general shape of a time series rather than standard distance of function (value) comparison. The new distance was used in classification with the nearest neighbor rule. Now we improve on our previous technique by adding the second derivative. In order to provide a comprehensive comparison, we conducted a set of experiments, testing effectiveness on 47 time series datasets from a wide variety of application domains. Our experiments show that this new method provides a significantly more accurate classification on the examined datasets. 相似文献
138.
In this article we review and compare a number of existing tests for detecting randomness in time series data, with emphasis on stock market index data. By comparing variance ratio tests with traditional statistical tests, we have the most extensive simulation comparison of such procedures. The investigated tests are compared over a diverse group of distributions, models, and stock market applications. In our stock market data analysis, the choice of data transformation can have a noticeable effect on test results. This study provides the reader with a guide as to which test and transformation is most appropriate for their use. 相似文献
139.
Estimation of a characteristic based on surveys repeated at regular intervals is considered. A state space formulation is given for the problem and the Kalman Filter is used to obtain an estimate and its variance. Some examples are also given to illustrate the methodology. 相似文献
140.
The principal components analysis (PCA) in the frequency domain of a stationary p-dimensional time series (X n ) n∈? leads to a summarizing time series written as a linear combination series X′ n =∑ m C m ° X n?m . Therefore, we observe that, when the coefficients C m , m≠0, are close to 0, this PCA is close to the usual PCA, that is the PCA in the temporal domain. When the coefficients tend to 0, the corresponding limit is said to satisfy a property noted 𝒫, of which we will study the consequences. Finally, we will examine, for any series, the proximity between the two PCAs. 相似文献