Results 71 to 80 of about 117,059 (160)

MCVIS: A New Framework for Collinearity Discovery, Diagnostic, and Visualization

, 2020
Collinearity discovery through diagnostic tools is an important analysis step when performing linear regression. Despite their wide-spread use, collinearity indices such as the variance inflation factor and the condition number have limitations and may ...
Chen Lin (95910), Kevin Wang (253690), Samuel Mueller (9268955)   +2 more
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Evaluation of Risk Factors for Chronic Obstructive Pulmonary Disease in the Middle-Aged and Elderly Rural Population of Northeast China Using Logistic Regression and Principal Component Analysis

Risk Management and Healthcare Policy, 2022
Rui Wang,1– 4 Wei Zhang,1– 3 Yuanyuan Li,1– 3 Yuting Jiang,1– 3 Hongqi Feng,1– 3 Yang Du,1– 3 Zhe Jiao,1– 3 Li Lan,4 Xiaona Liu,1– 3 Bingyun Li,1– 3 Chang Liu,1– 3 Xingbo Gu,5 Fang Chu,1– 3 Yuncheng Shen,1– 3 Chenpeng Zhu,1– 3 Xinhua Shao,1– 3 Simeng ...
Wang R, Zhang W, Li Y, Jiang Y, Feng H, Du Y, Jiao Z, Lan L, Liu X, Li B, Liu C, Gu X, Chu F, Shen Y, Zhu C, Shao X, Tong S, Sun D   +17 more
doaj  

Collinearity in generalized linear models

, 1986
The concept of collinearity for generalized linear models is introduced and compared to that for standard linear models. Two approaches for detecting collinearity are presented and shown to lead to the same diagnostic procedure.
Mackinnon, Murray J.
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The Collinearity Structure

, 2008
Summary. The text includes basic axioms and theorems concerning the collinearity structure based on Wanda Szmielew [1], pp. 18-20. Collinearity is defined as a relation on Cartesian product [:S, S, S:] of set S.
Wojciech Skaba, Université Catholique De Louvain   +1 more
core  

Analysis of collinearity among 19 climate variables.

Collinearity matrix of candidate R. sibiricus predictor climate variables. Collinearity threshold is R > 0.75. Collinearity of variables increases with the depth of blue and red colors. Correlation strength increases with circle size. (TIF)
Baozhu Dong (14200568), Xiaoqing Zhu (2397445), Hongyou Zhou (12280797), Jinyu Fan (168551), Wanyou Liu (17816823), Huanwen Meng (296360)   +5 more
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Collinearity for sensor network localization

, 2003
In the context of Wireless Sensors Networks, the knowledge of the device positions with the minimum possible error is required. In this paper we estimate sensor node positions throughout the measurement of the received powers from nodes characterized
POGGI, Cristian, MAZZINI, Gianluca
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Minimizing the effects of overfitting and collinearity in construction cost estimation : a new hybird approach

, 2014
Research problem: Overfitting and collinearity problems commonly exist in current construction cost estimation applications and obstruct researchers and practitioners in achieving better modelling results.
Xiong, Bo
core  

Analysis of collinearity among soil variables.

Collinearity matrix of candidate R. sibiricus predictor soil variables. Collinearity threshold is R > 0.75. Collinearity of variables increases with the depth of blue and red colors. Correlation strength increases with circle size. (TIF)
Baozhu Dong (14200568), Xiaoqing Zhu (2397445), Hongyou Zhou (12280797), Jinyu Fan (168551), Wanyou Liu (17816823), Huanwen Meng (296360)   +5 more
core   +1 more source

Diagnostics, Implications and Handling of Collinearity in Linear Models [PDF]

This thesis addresses the issue of collinearity in explanatory linear regression models, where the magnitude and sign of model coeficient estimates are crucial for meaningful interpretation. If collinearity is left unaddressed, it can distort statistical
Haibach, Lillemor
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Testing Collinearity of Vector Time Series

, 2019
We investigate the collinearity of vector time series in the frequency domain, by examining the rank of the spectral density matrix at a given frequency of interest. Rank reduction corresponds to collinearity at the given frequency.
Jach, Agnieszka, McElroy, Tucker S.
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