搜索结果: 1-15 共查到“M - ESTIMATORS”相关记录185条 . 查询时间(0.109 秒)
昆明理工大学理学院概率论与数理统计课件Chapter 7 Estimation Problems--The particular properties of estimators
昆明理工大学理学院 概率论与数理统计 课件 Chapter 7 Estimation Problems The particular properties of estimators
2017/4/17
昆明理工大学理学院概率论与数理统计课件Chapter 7 Estimation Problems--The particular properties of estimators.
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...
Quasi-Optimal Cardinality of AFEM Driven by Nonresidual Estimators
Error reduction convergence optimal cardinality adaptive algorithm
2015/12/11
We examine adaptive finite element methods (AFEM) with any polynomial degree satisfying rather general assumptions on the a posteriori error estimators. We show that several non-residual estimat...
L-estimators and m-estimators for doubly censored data
Asymptotic normality asymptotic variance Fredholm integral equation Hadamard differentiability self-consistent estimator strong consistency
2015/12/11
Motivated by estimation and testing with doubly censored data, we study (robust) Lestimators and M-estimators based on such data. These estimators are given through functionals of the self-consistent ...
On self-consistent estimators and kernel density estimators with doubly censored data
Asymptotic normality Failure rate function Right censored data: Survival distribution Uniform strong consistency
2015/12/11
We study the detailed structure (in a large sample) of the self-consistent estimators of the survival functions with doubly censored data. We also introduce the kernel-type density estimators based on...
STATISTICAL PROPERTIES OF MEAN STAND BIOMASS ESTIMATORS IN A LIDARBASED DOUBLE SAMPLING FOREST SURVEY DESIGN
Forestry statistics LIDAR sampling inventory biomass
2015/11/10
Airborne laser scanning (lidar) can be a valuable tool in double-sampling forest survey designs. Lidar-derived forest structure metrics are often highly correlated with important forest inventory vari...
On the finite sample properties of pre-test estimators of spatial models
Spatial models Spatial lag models
2015/9/24
This paper explores the properties of pre-test strategies in estimating a linear Cliff–Ord-type spatial model when
the researcher is unsure about the nature of the spatial dependence. More speciʂ...
Maximum likelihood and generalized spatial two-stage least-squares estimators for a spatial-autoregressive model with spatial-autoregressive disturbances
spreg spatial-autoregressive models
2015/9/24
We describe the spreg command, which implements a maximum
likelihood estimator and a generalized spatial two-stage least-squares estimator
for the parameters of a linear cross-sectional spatial-auto...
Finite sample properties of estimators of spatial autoregressive models with autoregressive disturbances
Spatial autoregressive models ordinary least squares two-stage least squares maximum likelihood finite sample distribution
2015/9/24
The article investigates the finite sample properties of estimators for spatial autoregressive models where the disturbance terms may follow a spatial autoregressive process. In particular we investig...
Higher Order Properties of Bootstrap and Jackknife Bias Corrected Maximum Likelihood Estimators
Bootstrap and Jackknife Bias Likelihood Estimators
2015/9/22
Pfanzagl and Wefelmeyer (1978) show that bias corrected ML estimators are higher order efficient.
Their procedure however is computationally complicated because it requires integrating complicat...
MEAN SQUARED ERROR REDUCTION FOR GMM ESTIMATORS OF LINEAR TIME SERIES MODELS
GMM LINEAR TIME SERIES MODELS
2015/9/22
In this paper we analyze Generalized Method of Moments (GMM) estimators for time
series models as advocated by Hansen and Singleton. It is well known that these estimators
achieve efficiency bo...
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections
dimension reduction l1 norm Johnson-Lindenstrauss (JL) lemma Cauchy random projections
2015/8/21
For1 dimension reduction in the l1 norm, the method of Cauchy random projections multiplies the original data matrix A ∈ Rn×D with a random matrix R ∈ RD×k (k D) whose entries are i.i.d. samples of ...
ASYMPTOTIC MINIMAXITY OF WAVELET ESTIMATORS WITH SAMPLED DATA
Besov spaces bounded operators between Besov spaces
2015/8/20
Donoho and Johnstone (1998) studied a setting where data were obtained
in the continuum white noise model and showed that scalar nonlinearities applied
to wavelet coefficients gave estimators w...
ON INCONSISTENT M-ESTIMATORS.
Derandomizing and Rerandomizing Variance Estimators
Derandomizing Rerandomizing Variance Estimators
2015/7/8
This technical report is meant to accompany the paper [7] and should be read in conjuction with that work. It describes several concepts which were alluded to in [7] but not elaborated on.
We give al...