搜索结果: 1-15 共查到“统计学其他学科 S-estimators”相关记录17条 . 查询时间(0.091 秒)
Practical Tikhonov Regularized Estimators in Reproducing Kernel Hilbert Spaces for Statistical Inverse Problems
Tikhonov Regularized Estimators Reproducing Kernel Hilbert Spaces Statistical Inverse Problems
2013/6/13
Regularized kernel methods such as support vector machines (SVM) and support vector regression (SVR) constitute a broad and flexible class of methods which are theoretically well investigated and comm...
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters
Dependent Dirichlet Priors Optimal Linear Estimators Belief Net Parameters
2012/9/19
A Bayesian belief network is a model of a joint distribution over a finite set of vari-ables, with a DAG structure representing im-mediate dependencies among the variables.For each node, a table of pa...
A note on extreme values and kernel estimators of sample boundaries
support estimation asymptotic normality kernel estimator ex-treme values.
2012/9/18
In a previous paper [3], we studied a kernel estimate of the upper edge of a two-dimensional bounded set, based upon the extreme values of a Poisson point process. The initial paper [1] on the subject...
Nonsingular subsampling for S-estimators with categorical predictors
Nonsingular subsampling S-estimators categorical predictors
2012/9/18
An integral part of many algorithms for S-estimators of linear regression is random subsam-pling. For problems with only continuous predictors simplerandom subsampling is a reliable method to generate...
A uniform central limit theorem and efficiency for deconvolution estimators
Deconvolution Donsker theorem Efficiency Distribution function Smoothed empirical processes Fourier multiplier
2012/9/17
We estimate linear functionals in the classical deconvolution problem by kernel esti-mators. We obtain a uniform central limit theorem with √n–rate on the assumption that the smoothness of the functio...
Aggregating density estimators: an empirical study
Machine Learning Histogram Kernel Density Estimator Bootstrap,Bagging Boosting, Stacking.
2012/9/19
We present some new density estimation algorithms obtainedby bootstrap ag-gregation like Bagging. Our algorithms are analyzed and empirically compared to other methods found in the statistical literat...
Estimators for Archimedean copulas in high dimensions: A comparison
Archimedean copulas parameter estimation Kendall’s tau Blomqvist’s beta minimum distance estimators (diagonal/simulated) maximum-likelihood estimation.
2012/9/19
The performance of known and new parametric estimators for Archimedean copulas is investigated, with special focus on large dimensions. In particular,method-of-moments-like estimators based on pairwis...
Efficient Estimators for Sequential and Resolution-Limited Inverse Problems
deconvolution ill-posed image processing sig-nal recovery
2012/9/18
A common problem in the sciences is that a signal of interest is observed only indirectly, through smooth functionals of the signal whose values are then obscured by noise. In suchinverse problems, th...
Bias correction for estimators of the extremal index
absolute regularity clustering of extremes extremal index
2011/7/19
We investigate the joint asymptotic behavior of so-called blocks estimator of the extremal index, that determines the mean length of clusters of extremes, based on the exceedances over different thres...
Smoothing ℓ₁-penalized estimators for high-dimensional time-course data
Lasso Local least squares Multivariate regression Variable selection Weighted likelihood
2009/9/16
When a series of (related) linear models has to be estimated it is often appropriate to combine the different data-sets to construct more efficient estimators. We use ℓ₁-penalized estimato...
Parameter estimation of ODE's via nonparametric estimators
Asymptotics M-estimator Nonparametric regression Parametric estimation Splines
2009/9/16
Ordinary differential equations (ODE's) are widespread models in physics, chemistry and biology. In particular, this mathematical formalism is used for describing the evolution of complex systems and ...
A class of unbiased location invariant Hill-type estimators for heavy tailed distributions
Asymptotic normality Location invariant Hilltype heavy tailed index estimator Second order regular variation
2009/9/16
Based on the methods provided in Caeiro and Gomes (2002) and Fraga Alves (2001), a new class of location invariant Hill-type estimators is derived in this paper. Its asymptotic distributional represen...
Case-deletion importance sampling estimators: Central limit theorems and related results
Infinite Variance Influence Leverage Marginal Residual Sum of Squares Markov Chain Monte Carlo Model Averaging Moment Index Tail Behavior
2009/9/16
Case-deleted analysis is a popular method for evaluating the influence of a subset of cases on inference. The use of Monte Carlo estimation strategies in complicated Bayesian settings leads naturally ...
Structural shrinkage of nonparametric spectral estimators for multivariate time series
structural shrinkage nonparametric spectral estimators multivariate time series
2009/9/16
In this paper we investigate the performance of periodogram based estimators of the spectral density matrix of possibly high-dimensional time series. We suggest and study shrinkage as a remedy against...
Uniform limit laws of the logarithm for estimators of the additive regression function in the presence of right censored data
nonparametric estimation additive regression function censored data uniform laws of the logarithm
2009/9/16
It has been recently shown that nonparametric estimators of the additive regression function could be obtained in the presence of right censoring by coupling the marginal integration method with initi...