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Orthogonal linear regression in Roentgen stereophotogrammetry
mathematical photogrammetry projective geometry
2010/9/15
Rooted in aerial reconnaissance, mathematical photogrammetry has evolved into a mainstay of biomedical image processing. The present paper develops an algorithm for Roentgen stereophotogrammetry, a me...
STRONG CONSISTENCY OF M-ESTIMATES OF MULTIPLE REGRESSION COEFFICIENTS
Linear regression M-estimate strong co
2007/12/17
In the case where ρ is convex we give a set of sufficient conditions for the strong consistency of M-estimate of multiple regression coefficients.
OPTIMAL GLOBAL RATES OF CONVERGENCE OF M-ESTIMATES FOR NONPARAMETRIC REGRESSION
Nonparametric regression optimal rate o
2007/12/17
Let (X, Y) be a pair of random variables such that X ranges over [0, 1] and Y is real-valued and let go(X) be the conditional expectation of Y given X. Based on a training sample, the piecewise polyno...
Consider the partly linear regression model y_i = x'_iβ + g(t_i) + ε_i, 1 ≤ i ≤ n, where y_i's are responses, x_i = (x_i1,x_i2,…,x_ip)＇ and t_i ∈ Τ are known and nonrandom design Τ is a compact set in...
Coverage Accuracy of Confidence Intervals in Nonparametric Regression
confidence interval empirical likelihood
2007/12/11
Point-wise confidence intervals for a nonparametric regression function with random design points are considered. The confidence intervals are those based on the traditional normal approximation and t...
DATA PREORDERING IN GENERALIZED PAV ALGORITHM FOR MONOTONIC REGRESSION
Quadratic programming Large scale optimization Least distance problem Monotonic regression Partially ordered data set Pool-adjacent-violators algorithm
2007/12/11
Monotonic regression (MR) is a least distance problem with
monotonicity constraints induced by a partially ordered data set of
observations. In our recent publication [In Ser. {\sl Nonconvex
Optimi...
Spatial Nonparametric Regression Estimation: Non-isotropic Case
bandwidth kernel estimator mixing non-isotropic
2007/12/11
Data collected on the surface of the earth often has spatial interaction. In this paper, a non-isotropic mixing spatial data process is introduced, and under such a spatial structure a nonparametric k...
The Minimax Estimator of Stochastic Regression Coecients and Parameters in the Class of All Estimators
minimax estimator stochastic regression coefficients quadratic loss function normal linear model
2007/12/11
In this paper, the authors address the problem of the minimax estimator of linear combinations of stochastic regression coefficients and parameters in the general normal linear model with random effec...
Delete-group Jackknife Estimate in Partially Linear Regression Models with Heteroscedasticity
partially linear regression model asymptotic variance
2007/12/10
Consider a partially linear regression model with an unknown vector parameter β, an unknown function g(·), and unknown heteroscedastic error variances. Chen, You~([23]) proposed a semiparametric gener...
EXISTENCE OF CONSISTENT ESTIMATES OF LINEAR REGRESSION COEFFICIENTS WHEN THE ERROR VARIANCES ARE UNEQUAL
Linear regression model consistency
2007/12/10
摘要 Consider the linear regression model Y_i=x_i′β+σ_ie_i,i=1,…,n,…, where E(e_i)=0, E(e_ie_j)=δ_(ij), 00. This paper shows that (i) if σ_i~2,i=1,2…, are known, then the necessary and sufficient condit...
CO2 flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression
CO2 flux determination closed-chamber methods linear regression
2010/1/14
Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or v...
Phase Space Prediction of Chaotic Time Series with Nu-Support Vector
Machine Regression
chaotic time series phase space prediction support vector machines
2007/8/15
2005Vol.43No.1pp.102-106DOI:
Phase Space Prediction of Chaotic Time Series with Nu-Support Vector
Machine Regression
YE Mei-Ying1 and WANG Xiao-Dong2
1 College of Mathem...
NONMRAMETRIC AND SEMIPARAMETRIC REGRESSION MODELS WITH LOCALLY GENERALIZED GAUSSIAN ERROR
Nonparametric semiparametric regression
2007/8/7
Under a locally generalized Gaussian error's structure, we obtain strong uniform consistency for nonparametric regression function estimators and strong consistency for parametric component estimators...
DIAGNOSTICS FOR NONLINEAR REGRESSION MODEL WITH WEIGHTING OR TRANSFORMATION
Box-Cox transformation case-deletion mo
2007/8/7
In this paper, we propose several diagnostic measures for assessing the influence of an individual case and small perturbations on the transformation power estimator and the variance function estimato...