搜索结果: 1-11 共查到“理论统计学 Smoothing”相关记录11条 . 查询时间(0.156 秒)
On Smoothing Estimation For Seasonal Times Series With Long Cycles
Large deviation Large p, small n Optimal detection boundary Sparse signal Thresholding Weak dependence
2016/1/25
We consider two alternative tests to the Higher Criticism test of Donoho and Jin (2004) for high dimensional means under the spar-sity of the non-zero means for sub-Gaussian distributed data with unkn...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/20
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
On Smoothing Estimation For Seasonal Times Series With Long Cycles
Kernel estimator M-dependent seasonal-dummy ap- proach
2016/1/20
We consider a kernel smoothing estimator to the periodic component of seasonal time series which have quite large periodicity relative to the length of the time series. The estimator is formulated by ...
Optimization viewpoint on Kalman smoothing, with applications to robust and sparse estimation
Optimization viewpoint Kalman smoothing applications robust sparse estimation
2013/4/28
In this paper, we present the optimization formulation of the Kalman filtering and smoothing problems, and use this perspective to develop a variety of extensions and applications. We first formulate ...
Smoothing effect of Compound Poisson approximation to distribution of weighted sums
characteristic function concentration function compound Poisson distribution Kolmogorov norm weighted random variables.
2013/4/27
The accuracy of compound Poisson approximation to the sum $S=w_1S_1+w_2S_2+...+w_NS_N$ is estimated.
Here $S_i$ are sums of independent or weakly dependent random variables, and $w_i$ denote weights...
Bayesian Adaptive Smoothing Spline using Stochastic Differential Equations
Adaptive smoothing Markov chain Monte Carlo Smoothing spline Stochastic dierential equation
2012/11/22
The smoothing spline is one of the most popular curve-fitting methods, partly because of empirical evidence supporting its effectiveness and partly because of its elegant mathematical formulation. How...
Iterative bias reduction multivariate smoothing in R: The ibr package
multivariate smoothing L2 boosting thin-plate splines kernel regression R
2011/6/20
In multivariate nonparametric analysis, sparseness of the co-
variates also called curse of dimensionality, forces one to use large smoothing
parameters. This leads to a biased smoother. Instead of ...
Smoothed ANOVA with spatial effects as a competitor to MCAR in multivariate spatial smoothing
Analysis of variance Bayesian inference conditionally autore gressive model hierarchical model smoothing
2010/11/8
Rapid developments in geographical information systems (GIS)continue to generate interest in analyzing complex spatial datasets.One area of activity is in creating smoothed disease maps to de-scribe t...
Particle Learning and Smoothing
Mixture Kalman filter parameter learning particle learning sequential inference smoothing state filtering
2010/11/9
Particle learning (PL) provides state filtering, sequential parameter learning and smoothing in a general class of state space models.Our approach extends existing particle methods by incorporating th...
Smoothing splines estimators for functional linear regression
Functional linear regression functional parameter functionalvariable smoothing splines
2010/3/18
The paper considers functional linear regression, where scalar responses
Y1, . . . ,Yn are modeled in dependence of random functions
X1, . . . ,Xn. We propose a smoothing splines estimator for the f...
Component selection and smoothing in multivariate nonparametric regression
Smoothing spline ANOVA method of regularization nonparametricregression nonparametric classification model selection
2010/4/26
We propose a new method for model selection and model fitting
in multivariate nonparametric regression models, in the framework
of smoothing spline ANOVA. The “COSSO” is a method of
regularization ...