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排序方式: 共有1681条查询结果,搜索用时 31 毫秒
1.
This article considers statistical inference for the heteroscedastic partially linear varying coefficient models. We construct an efficient estimator for the parametric component by applying the weighted profile least-squares approach, and show that it is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator reaches the semiparametric efficiency bound. Simulation studies are conducted to illustrate the performance of the proposed method. 相似文献
2.
Laurent Gardes Stéphane Girard Gilles Stupfler 《Scandinavian Journal of Statistics》2020,47(3):922-949
The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail Lp-medians encompassing the MS and CTE. For p in (1,2), a tail Lp-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data. 相似文献
3.
Abstract. We correct two proofs concerning Markov properties for graphs representing marginal independence relations. 相似文献
4.
Gabriela Beganu 《Statistical Methods and Applications》2007,16(3):347-356
It is known that the Henderson Method III (Biometrics 9:226–252, 1953) is of special interest for the mixed linear models
because the estimators of the variance components are unaffected by the parameters of the fixed factor (or factors). This
article deals with generalizations and minor extensions of the results obtained for the univariate linear models. A MANOVA
mixed model is presented in a convenient form and the covariance components estimators are given on finite dimensional linear
spaces. The results use both the usual parametric representations and the coordinate-free approach of Kruskal (Ann Math Statist
39:70–75, 1968) and Eaton (Ann Math Statist 41:528–538, 1970). The normal equations are generalized and it is given a necessary
and sufficient condition for the existence of quadratic unbiased estimators for covariance components in the considered model. 相似文献
5.
首先分析了对数最小二乘排序法的特点,说明它是一种值得重视的好方法;并进一步阐述了这一方法的基本原理,着重地对群体判断下求加权的综合排序向量的方法进行了严密的数学推导;提出了在加权的综合排序中权重系数确定的新見解,并举例子以解释。 相似文献
6.
利用漫反射法获得环丙沙星短波近红外光谱(700-1100nm),采用化学计量学中的偏最小二乘法(PLS),选取不同的波长范围及不同的光谱预处理方法(一阶导数和和二阶导数)对光谱进行信息提取和分析,对盐酸环丙沙星粉末药品进行了无损非破坏定量分析,以样品中盐酸环丙沙星为活性成分建立了最佳的数学校正模型。讨论了主成分数对PLS模型定量预测能力的影响,并做了比较。 相似文献
7.
Summary Weak disintegrations are investigated from various points of view. Kolmogorov's definition of conditional probability is critically
analysed, and it is noted how the notion of disintegrability plays some role in connecting Kolmogorov's definition with the
one given in line with de Finetti's coherence principle. Conditions are given, on the domain of a prevision, implying the
equivalence between weak disintegrability and conglomerability. Moreover, weak sintegrations are characterized in terms of
coherence, in de Finetti's sense, of, a suitable function. This fact enables us to give, an interpretation of weak disintegrability
as a form of “preservation of coherence”. The previous results are also applied to a hypothetical inferential problem. In
particular, an inference is shown to be coherent, in the sense of Heath and Sudderth, if and only if a suitable function is
coherent, in de Finetti's sense.
Research partially supported by: M.U.R.S.T. 40% “Problemi di inferenza pura”. 相似文献
8.
A. Baddeley R. Turner J. Møller M. Hazelton 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2005,67(5):617-666
Summary. We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q – Q -plots of the residuals are effective in diagnosing interpoint interaction. 相似文献
9.
Summary The paper deals with missing data and forecasting problems in multivariate time series making use of the Common Components
Dynamic Linear Model (DLMCC), presented in Quintana (1985), and West and Harrison (1989).
Some results are presented and discussed: exploiting the correlation between series, estimated by the DLMCC, the paper shows
as it is possible to update state vector posterior distributions for the unobserved series. This is realized on the base of
the updating of the observed series state vectors, for which the usual Kalman filter equations can be applied.
An application concerning some Italian private consumption series provides an example of the model capabilities. 相似文献
10.
The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators. 相似文献