搜索结果: 1-15 共查到“理论统计学 M-estimators”相关记录71条 . 查询时间(0.109 秒)
One may consider a discrete-event simulation as a Markov chain evolving on a suitably rich state space. One way that regenerative cycles may be constructed for general state-space Markov chains is to ...
On model selection consistency of M-estimators with geometrically decomposable penalties
model selection consistency M-estimators geometrically decomposable penalties
2013/6/14
Penalized M-estimators are used in many areas of science and engineering to fit models with some low-dimensional structure in high-dimensional settings. In many problems arising in bioinformatics, sig...
Limit theorems for kernel density estimators under dependent samples
Kernel density estimator consistency convergence rate mixing rate
2013/6/14
In this paper, we construct a moment inequality for mixing dependent random variables, it is of independent interest. As applications, the consistency of the kernel density estimation is investigated....
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
Regularized M-estimators nonconvexity Statistical algorithmic theory local optima
2013/6/14
We establish theoretical results concerning all local optima of various regularized M-estimators, where both loss and penalty functions are allowed to be nonconvex. Our results show that as long as th...
A General Family of Estimators for Estimating Population Mean in Systematic Sampling Using Auxiliary Information in the Presence of Missing Observations
Family of estimators Auxiliary information Mean square error Non-response Systematic sampling
2013/6/14
This paper proposes a general family of estimators for estimating the population mean in systematic sampling in the presence of non-response adapting the family of estimators proposed by Khoshnevisan ...
Central limit theorems for pre-averaging covariance estimators under endogenous sampling times
Central limit theorem Hitting times Market microstructure noise Nonsynchronous observa-tions Pre-averaging Time endogeneity
2013/6/13
We consider two continuous It\^o semimartingales observed with noise and sampled at stopping times in a nonsynchronous manner. In this article we establish a central limit theorem for the pre-averaged...
Calculation of Exact Estimators by Integration Over the Surface of an n-Dimensional Sphere
Calculation Exact Estimators Integration Over the Surface an n-Dimensional Sphere
2013/6/13
This paper reconsiders the problem of calculating the expected set of probabilities , given the observed set of items {m_i}, that are distributed among n bins with an (unknown) set of probabiliti...
Asymptotic normality and efficiency of two Sobol index estimators
sensitivity analysis Sobol indices asymptotic efficiency asymptotic normality confidence intervals metamodelling surface response methodology
2013/4/28
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
Asymptotics for penalized spline estimators in quantile regression
Asymptotic normality, B-spline,Penalized spline,Quantile regression
2012/11/22
Quantile regression predicts the $\tau$-quantile of the conditional distribution of a response variable given the explanatory variable for $\tau\in(0,1)$. The aim of this paper is to establish the asy...
Shrinkage estimators for prediction out-of-sample: Conditional performance
James-Stein estimator rando mmatrix theory random design
2012/11/22
We find that, in a linear model, the James-Stein estimator, which dominates the maximum-likelihood estimator in terms of its in-sample prediction error, can perform poorly compared to the maximum-like...
In this paper we propose a family of robust estimates for isotonic regression: isotonic M-estimators.
We show that their asymptotic distribution is, up to an scalar factor, the same as that of Brunk ...
Asymptotic Behaviour of Approximate Bayesian Estimators
Parameter Estimation Hidden Markov Model Maximum Likelihood Approximate Bayesian Computation Sequential Monte Carlo
2011/6/20
Although approximate Bayesian computation (ABC) has become
a popular technique for performing parameter estimation when the
likelihood functions are analytically intractable there has not as yet
be...
Delta method in large deviations and moderate deviations for estimators
Delta method hypothesis testing Kaplan–Meier estimator large deviations L-statistics M-estimator moderate deviations
2011/6/20
The delta method is a popular and elementary tool for deriving
limiting distributions of transformed statistics, while applications of
asymptotic distributions do not allow one to obtain desirable a...
Consistency of maximum-likelihood and variational estimators in the Stochastic Block Model
maximum-likelihood Stochastic Block Model
2011/6/17
The stochastic block model (SBM) is a probabilistic model de-
signed to describe heterogeneous directed and undirected graphs. In this
paper, we address the asymptotic inference on SBM by use of max...
Geometric sensitivity of random matrix results: consequences for shrinkage estimators of covariance and related statistical methods
random matrix related statistical shrinkage estimators
2011/6/16
Shrinkage estimators of covariance are an important tool in modern applied and theoretical statistics.
They play a key role in regularized estimation problems, such as ridge regression (aka Tykhonov
...
