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An Exact Test for Multiple Inequality and Equality Constraints in the Linear Regression Model
Multiple Inequality Equality Constraints
2015/7/31
In this article we consider the linear regression model y = X,B + a,
where e is N(O, a21). In this context we derive exact tests of the form
H: Rft ? r versus K: f E R K for the case in which a2 i...
Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces
Diverging number of parameters Feature selection Extended Bayes information criterion High dimensional feature space
2011/9/5
Abstract: In many conventional scientific investigations with high or ultra-high dimensional feature spaces, the relevant features, though sparse, are large in number compared with classical statistic...
The Hannan-Quinn Proposition for Linear Regression
Hannan-Quinn linear regression the law of iterated logarithms strong consistency
2011/2/23
We consider the variable selection problem in linear regression. Suppose that we have a set
of random variables X1, · · · ,Xm, Y, ǫ such that Y = Pk2 αkXk +ǫ with π ⊆ {1, · · · ,m} a...
Evaluation of Various Linear Regression Methods for Downscaling of Mean Monthly Precipitation in Arid Pichola Watershed
Backward Forward Precipitation Regression Stepwise
2013/3/8
In this paper, downscaling models are developed using various linear regression approaches namely direct, forward, backward and stepwise regression for downscaling of GCM output to predict mean monthl...
Evaluation of Various Linear Regression Methods for Downscaling of Mean Monthly Precipitation in Arid Pichola Watershed
Backward Forward Precipitation Regression Stepwise
2013/3/8
In this paper, downscaling models are developed using various linear regression approaches namely direct, forward, backward and stepwise regression for downscaling of GCM output to predict mean monthl...
A multiple linear regression GIS module using spatial variables to model orographic rainfall
multiple linear regression GIS module spatial variables orographic rainfall
2009/12/4
This paper aims to document the development of a new GIS-based spatial interpolation module that adopts a multiple linear regression technique. The functionality of the GIS module is illustrated throu...
Modelling longwave radiation to snow beneath forest canopies using hemispherical photography or linear regression
forest snow canopy radiation modelling longwave radiation hemispherical photography
2014/4/3
Forest canopies reduce shortwave radiation and increase longwave radiation reaching the underlying surface, compared with
open areas, and thus influence rates at which forest snowpacks melt. Th...
Fuzzy linear regression models with fuzzy entropy
Fuzzy numbers Fuzzy linear regression Fuzzy entropy
2010/9/15
Fuzzy regression analysis using fuzzy linear models with symmetric triangular fuzzy number coefficient has been introduced by Tanaka et al.The goal of this regression is to find the coefficient of a p...
Exact distributions for sensitivity analysis in linear regression
Diagnostic outlier Cook’s distance elliptical law
2010/9/15
Based on a multivariate linear regression model, we propose several generalizations to the multivariate classical and modified Cook’s distances in order to detect one or more influential observations ...
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...
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...
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...
A FAST PROCEDURE OF VARIABLE SELECTION IN LINEAR REGRESSION MODEL
Linear regression optimal subset a.s.l
2007/8/7
In many situations, we are interested in selection of important variables whichare adequate for prediction under a linear regression model. In this paper, a fast selection procedure is proposed and is...