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Properties of Census Dual System Population Size Estimators
Capture-recapture Correlation Bias Erroneous enumeration Kernel smooth- ing Model bias
2016/1/19
We evaluate three population size estimators, including the post-stratification and lo-gistic regression estimators which has been or will be implemented in the US Census dual system surveys. Conditio...
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...
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...
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...
On the impossibility of constructing good population mean estimators in a realistic Respondent Driven Sampling model
impossibility constructing good population mean estimators realistic Respondent Driven Sampling model
2012/11/22
Current methods for population mean estimation from data collected by Respondent Driven Sampling (RDS) are based on the Horvitz-Thompson estimator together with a set of assumptions on the sampling mo...
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...
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...