نتایج جستجو برای: multi collinearity

تعداد نتایج: 465996  

2004
Dong Jung Kang

This paper presents an effective recognition method based on perceptual organization of low level features detected in an image. The method uses a dynamic programming (DP) based formulation to represent various line groups such as convex, concave, and more complex patterns consisting of convex and concave shapes. The essential features of perceptual organization such as endpoint proximity, coll...

2015
Arezoo BAGHERI Arezoo Bagheri

the latest known source of multicollinearity, a nonorthogonality of two or more explanatory variables in multiple regression models, is high leverage points. Interpreting a fitted regression model may become impossible by the influential impacts of multicollinearity. In this paper, we attempt to investigate the impact of different sample sizes as one of the main causing factors of high leverage...

Journal: :Pattern Recognition Letters 1982
Leslie J. Kitchen Azriel Rosenfeld

This report consists of two independent parts. The first is entitled "Non-maximum suppression of gradient magnitudes makes them easier to threshold"; it shows that, besides reducing thick responses to thin, the application of non-maximum suppression to digital gradient magnitudes also improves the form of the edge response histogram, making the choice of thresholds easier. In the second, entitl...

K. Kesavacharyulu K. Rajashekar M. Rekha

In mulberry (Morus sp.), grown for its foliage, which is the sole food for the silkworm (Bombyx mori L.), evolving high yielding varieties is a long drawn and laborious process. One of the important selection parameter that has significant positive correlation with leaf yield is Total Shoot Length [TSL] of the mulberry plant. Measuring the length of all the shoots of the test genotypes to get t...

2010
Dan Liao Richard Valliant

Survey data are often used to fit linear regression models. The values of covariates used in modeling are not controlled as they might be in an experiment. Thus, collinearity among the covariates is an inevitable problem in the analysis of survey data. Although many books and articles have described the collinearity problem and proposed strategies to understand, assess and handle its presence, ...

Journal: :GigaScience 2017
Robert Bukowski Xiaosen Guo Yanli Lu Cheng Zou Bing He Zhengqin Rong Bo Wang Dawen Xu Bicheng Yang Chuanxiao Xie Longjiang Fan Shibin Gao Xun Xu Gengyun Zhang Yingrui Li Yinping Jiao John F Doebley Jeffrey Ross-Ibarra Anne Lorant Vince Buffalo M Cinta Romay Edward S Buckler Doreen Ware Jinsheng Lai Qi Sun Yunbi Xu

Background Characterization of genetic variations in maize has been challenging, mainly due to deterioration of collinearity between individual genomes in the species. An international consortium of maize research groups combined resources to develop the maize haplotype version 3 (HapMap 3), built from whole genome sequencing data from 1,218 maize lines, covering pre-domestication and domestica...

2014
Lee H. Wurm Sebastiano A. Fisicaro

Psycholinguists are making increasing use of regression analyses and mixed-effects modeling. In an attempt to deal with concerns about collinearity, a number of researchers orthogonalize predictor variables by residualizing (i.e., by regressing one predictor onto another, and using the residuals as a stand-in for the original predictor). In the current study, the effects of residualizing predic...

2008
Hui Zou Hao Helen Zhang HUI ZOU HAO HELEN ZHANG

We consider the problem of model selection and estimation in situations where the number of parameters diverges with the sample size. When the dimension is high, an ideal method should have the oracle property (Fan and Li, 2001; Fan and Peng, 2004) which ensures the optimal large sample performance. Furthermore, the highdimensionality often induces the collinearity problem which should be prope...

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