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41.
讨论了一类发展方程——线性抛物型方程的窄四边形元逼近方法,导出了相应的半离散格式和全离散格式,并通过一些新的技巧,得到了相应的误差估计. 相似文献
42.
M. O. Salau 《Statistical Papers》2003,44(1):89-105
This paper investigates, by means of Monte Carlo simulation, the effects of different choices of order for autoregressive
approximation on the fully efficient parameter estimates for autoregressive moving average models. Four order selection criteria,
AIC, BIC, HQ and PKK, were compared and different model structures with varying sample sizes were used to contrast the performance
of the criteria. Some asymptotic results which provide a useful guide for assessing the performance of these criteria are
presented. The results of this comparison show that there are marked differences in the accuracy implied using these alternative
criteria in small sample situations and that it is preferable to apply BIC criterion, which leads to greater precision of
Gaussian likelihood estimates, in such cases. Implications of the findings of this study for the estimation of time series
models are highlighted. 相似文献
43.
Philip Rees Paul Norman Dominic Brown 《Journal of the Royal Statistical Society. Series A, (Statistics in Society)》2004,167(1):5-36
Summary. The paper presents a framework for small area population estimation that enables users to select a method that is fit for the purpose. The adjustments to input data that are needed before use are outlined, with emphasis on developing consistent time series of inputs. We show how geographical harmonization of small areas, which is crucial to comparisons over time, can be achieved. For two study regions, the East of England and Yorkshire and the Humber, the differences in output and consequences of adopting different methods are illustrated. The paper concludes with a discussion of how data, on stream since 1998, might be included in future small area estimates. 相似文献
44.
Y.P. Mack 《Journal of statistical planning and inference》1983,8(2):185-192
Let fn(x) be the univariate k-nearest neighbor (k-NN) density estimate proposed by Loftsgaarden and Quesenberry (1965). By using similar techniques as in Bahadur's representation of sample quantiles (1966), and by the recent results on the oscillation of empirical processes by Stute (1982), we derive the rate of strong uniform convergence of fn(x) on some suitably chosen interval Jδ. Some comparison with the kernel estimates is given, as well as the choice of the bandwidth sequence relative to the sample size. 相似文献
45.
Recursive estimates of a probability density function (pdf) are known. This paper presents recursive estimates of a derivative of any desired order of a pdf. Let f be a pdf on the real line and p?0 be any desired integer. Based on a random sample of size n from f, estimators f(p)n of f(p), the pth order derivatives of f, are exhibited. These estimators are of the form , where δjp depends only on p and the jth observation in the sample, and hence can be computed recursively as the sample size increases. These estimators are shown to be asymptotically unbiased, mean square consistent and strongly consistent, both at a point and uniformly on the real line. For pointwise properties, the conditions on f(p) have been weakened with a little stronger assumption on the kernel function. 相似文献
46.
This study examined the development of baserate estimation skills for everyday social events and attitudes. Subjects in grades one, three, and six responded to questions concerning their own rates of behavior and attitudes, and their estimates of baserates of behaviors and attitudes for their classmates. The findings indicate a general increase in accuracy for the estimation of baserates throughout the elementary school years. In addition, younger subjects were less likely to make similar estimates for themselves and their classmates than were older respondents. Developmental changes in estimation accuracy are discussed in relation to task content, use of the response scale, correspondence between self-reports and estimates, and sample variability. 相似文献
47.
For a moderate or large number of regression coefficients, shrinkage estimates towards an overall mean are obtained by Bayes and empirical Bayes methods. For a special case, the Bayes and empirical Bayes shrinking weights are shown to be asymptotically equivalent as the amount of shrinkage goes to zero. Based on comparisons between Bayes and empirical Bayes solutions, a modification of the empirical Bayes shrinking weights designed to guard against unreasonable overshrinking is suggested. A numerical example is given. 相似文献
48.
M. Samiuddin 《Australian & New Zealand Journal of Statistics》1982,24(2):211-215
A necessary and sufficient condition for unbiasedness of the test of homogeneity of variances in normal samples is derived in a convenient form. In the case of two samples, it is shown that Bartlett's test is the only unbiased test of homogeneity of variances. A simple alternative proof of the unbiasedness of Bartlett's test in the general case is also provided. 相似文献
49.
Smiley W. Cheng 《Journal of statistical planning and inference》1980,4(3):259-265
The asymptotically best linear unbiased estimate (ABLUE) of the normal mean is discussed. The estimate is based on k selected order statistics chosen from a singly or doubly censored large sample of size n(>k). The coefficients, the asymptotic relative efficiency of the estimate, and the optimum spacing of k real numbers between 0 and 1 which determines the optimum ranks of order statistics, are provided. A comparison between the ABLUE and the iterated maximum likelihood estimate is made. 相似文献
50.
The Dirichlet process prior allows flexible nonparametric mixture modeling. The number of mixture components is not specified
in advance and can grow as new data arrive. However, analyses based on the Dirichlet process prior are sensitive to the choice
of the parameters, including an infinite-dimensional distributional parameter G
0. Most previous applications have either fixed G
0 as a member of a parametric family or treated G
0 in a Bayesian fashion, using parametric prior specifications. In contrast, we have developed an adaptive nonparametric method
for constructing smooth estimates of G
0. We combine this method with a technique for estimating α, the other Dirichlet process parameter, that is inspired by an
existing characterization of its maximum-likelihood estimator. Together, these estimation procedures yield a flexible empirical
Bayes treatment of Dirichlet process mixtures. Such a treatment is useful in situations where smooth point estimates of G
0 are of intrinsic interest, or where the structure of G
0 cannot be conveniently modeled with the usual parametric prior families. Analysis of simulated and real-world datasets illustrates
the robustness of this approach. 相似文献