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91.
Abstract. We propose covariate adjusted correlation (Cadcor) analysis to target the correlation between two hidden variables that are observed after being multiplied by an unknown function of a common observable confounding variable. The distorting effects of this confounding may alter the correlation relation between the hidden variables. Covariate adjusted correlation analysis enables consistent estimation of this correlation, by targeting the definition of correlation through the slopes of the regressions of the hidden variables on each other and by establishing a connection to varying-coefficient regression. The asymptotic distribution of the resulting adjusted correlation estimate is established. These distribution results, when combined with proposed consistent estimates of the asymptotic variance, lead to the construction of approximate confidence intervals and inference for adjusted correlations. We illustrate our approach through an application to the Boston house price data. Finite sample properties of the proposed procedures are investigated through a simulation study. 相似文献
92.
Rasul A. Khan 《Journal of statistical planning and inference》1984,9(2):199-206
A subfamily of exponential distributions is considered and it is shown that the variance of the UMVU estimator of an estimable function g(θ) having power series expansion is the limit of Bhattacharya bounds. 相似文献
93.
R.A. MOYEED 《Australian & New Zealand Journal of Statistics》1995,37(2):193-204
The paper shows how a finite dimensional representation of a cubic smoothing spline can be put in the framework of a dynamic linear model. The formulation provides an updating scheme when observations do not occur sequentially in time or space. 相似文献
94.
ABSTRACT We present a method to approximate and forecast, on an entire interval, a continuous-time process. For this purpose, we use the modelization of ARH(l) processes, defined by Bosq (1991). We deal with the practical problem of the discretization of the observed trajectories and approximate them by means of spline functions. We show by simulations that for well-chosen smoothing parameters, good prediction can be obtained in comparison with the “predictable” part of the process. Finally, we apply this model to forecast road traffic and compare it with a SARIMA model. 相似文献
95.
Non-parametric Regression with Dependent Censored Data 总被引:1,自引:0,他引:1
Abstract. Let ( X i , Y i ) ( i = 1 ,…, n ) be n replications of a random vector ( X , Y ), where Y is supposed to be subject to random right censoring. The data ( X i , Y i ) are assumed to come from a stationary α -mixing process. We consider the problem of estimating the function m ( x ) = E ( φ ( Y ) | X = x ), for some known transformation φ . This problem is approached in the following way: first, we introduce a transformed variable , that is not subject to censoring and satisfies the relation , and then we estimate m ( x ) by applying local linear regression techniques. As a by-product, we obtain a general result on the uniform rate of convergence of kernel type estimators of functionals of an unknown distribution function, under strong mixing assumptions. 相似文献
96.
A smoothing procedure for discrete time failure data is proposed which allows for the inclusion of covariates. This purely nonparametric method is based on discrete or continuous kernel smoothing techniques that gives a compromise between the data and smoothness. The method may be used as an exploratory tool to uncover the underlying structure or as an alternative to parametric methods when prediction is the primary objective. Confidence intervals are considered and alternative techniques of cross validation based choices of smoothing parameters are investigated. 相似文献
97.
Principal components are a well established tool in dimension reduction. The extension to principal curves allows for general
smooth curves which pass through the middle of a multidimensional data cloud. In this paper local principal curves are introduced,
which are based on the localization of principal component analysis. The proposed algorithm is able to identify closed curves
as well as multiple curves which may or may not be connected. For the evaluation of the performance of principal curves as
tool for data reduction a measure of coverage is suggested. By use of simulated and real data sets the approach is compared
to various alternative concepts of principal curves. 相似文献
98.
The monitoring of process/product profiles is presently a growing and promising area of research in statistical process control. This study is aimed at developing monitoring schemes for nonlinear profiles with random effects. We utilize the technique of principal components analysis to analyze the covariance structure of the profiles and propose monitoring schemes based on principal component (PC) scores. The number of the PC scores used in constructing control charts is crucial to the detecting power. In the Phase I analysis of historical data, due to the dependency of the PC-scores, we adopt the usual Hotelling T 2 chart to check the stability. For Phase II monitoring, we study individual PC-score control charts, a combined chart scheme that combines all the PC-score charts, and a T 2 chart. Although an individual PC-score chart may be perfect for monitoring a particular mode of variation, a chart that can detect general shifts, such as the T 2 chart and the combined chart scheme, is more feasible in practice. The performances of the schemes under study are evaluated in terms of the average run length. 相似文献
99.
Johannes Ledolter 《统计学通讯:理论与方法》2013,42(6):959-971
Time series smoothers estimate the level of a time series at time t as its conditional expectation given present, past and future observations, with the smoothed value depending on the estimated time series model. Alternatively, local polynomial regressions on time can be used to estimate the level, with the implied smoothed value depending on the weight function and the bandwidth in the local linear least squares fit. In this article we compare the two smoothing approaches and describe their similarities. Through simulations, we assess the increase in the mean square error that results when approximating the estimated optimal time series smoother with the local regression estimate of the level. 相似文献
100.
We consider the problem of change-point in a classical framework while assuming a probability distribution for the change-point. An EM algorithm is proposed to estimate the distribution of the change-point. A change-point model for multiple profiles is also proposed, and EM algorithm is presented to estimate the model. Two examples of Illinois traffic data and Dow Jones Industrial Averages are used to demonstrate the proposed methods. 相似文献