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Pharyngometric correlations with obstructive sleep apnea syndrome

ACTA OTO-LARYNGOLOGICA 2004年第10期124卷 1182-1186页

作者： Thulesius, HL Thulesius, HO Jessen, M Cent Hosp Vaxjo ENT Dept SE-35185 Vaxjo Sweden Kronoberg Cty Res Ctr Vaxjo Sweden

Objective - The primary objective of this study was to investigate the relationship between obstructive sleep apnea syndrome (OSAS) and pharyngometric dimensions as clinical predictors of OSAS. Material and Methods - Pharyngometry included tonsil size, the breadth of the uvula (UB), the distance between the uvula and the posterior pharyngeal wall and open mouth standardized photographic measurement of the dimension of the free oropharynx ( FOP). We also assessed modified Mallampati grade (MMP). In addition, clinical data on body weight, height, nasal obstruction and cardiovascular disease were included in our analysis. Results - A total of 96 consecutive patients of both sexes with sleep disorders were investigated with somnography. Of these, 35 were considered to have OSAS, with an apnea - hypopnea index (AHI) of greater than or equal to10. Body mass index (BMI), FOP, UB, the use of cardiovascular medication and hypertension were significantly related to AHI, and tonsil size showed borderline significance. regression models were used to determine an OSAS index using the parameters BMI and FOP. The index had a positive predictive value of 82% and a negative predictive value of 77%. Conclusions - We showed that a photographic assessment of pharyngeal dimensions was significantly associated with OSAS. We also confirmed previous findings of associations between OSAS, BMI and cardiovascular morbidity.

关键词： body mass index cardiovascular morbidity clinical signs linear regression models sleep disorders symptom score upper respiratory obstruction

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Lasso for sparse linear regression with exponentially β-mixing errors

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STATISTICS & PROBABILITY LETTERS 2017年 125卷 64-70页

作者： Xie, Fang Xu, Lihu Yang, Youcai Univ Macau Dept Math Fac Sci & Technol Macau Peoples R China Qingdao Univ Sci & Technol Sch Econ & Management Qingdao Shandong Peoples R China

We prove two consistency theorems for the lasso estimators of sparse linear regression models with exponentially beta-mixing errors, in which the number of regressors p is large, even much larger than the sample size ... 详细信息

关键词： Lasso linear regression models Consistency Exponentially beta-mixing errors

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Bootstrap of minimum distance estimators in regression with correlated disturbances

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JOURNAL OF STATISTICAL PLANNING AND INFERENCE 2002年第1-2期108卷 283-299页

作者： Vilar-Fernández, JM Vilar-Fernández, JA Univ A Coruna Fac Informat Dept Matemat La Coruna 15071 Spain

The linear regression model Y-i = x(i)theta + epsilon(i), where x(i) is an element of R-p, theta is an unknown parameter vector and the observational errors epsilon(i) follow an AR(1) model, is considered. In a previous paper, Vilar-Fernandez and Gonzalez-Manteiga (Statist. Papers, to appear) have proposed a two-stage kgeneralized minimum distance estimator (GMD) for theta, which presents the same asymptotic properties as the generalized least-squares estimator (GLS). However, for finite samples, the GMD estimator has been shown to be more efficient in terms of the mean-squared error than the GLS one when the errors of the model are heavily correlated and with large variance. This paper establishes the consistency of a bootstrap procedure to approximate the distribution of the GMD estimator. In addition, the good behavior of the bootstrap approximation with respect to the asymptotic distribution of the GMD is shown in a simulation study. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： minimum distance estimators linear regression models nonparametric estimation bootstrap

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ROBUST ESTIMATION IN PARAMETRIC TIME SERIES models UNDER LONG- AND SHORT-RANGE-DEPENDENT STRUCTURES

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AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS 2009年第2期51卷 161-181页

作者： Gao, Jiti Li, Degui Lin, Zhengyan Univ Adelaide Sch Econ Adelaide SA 5005 Australia Zhejiang Univ Dept Math Hangzhou 310027 Peoples R China Univ Western Sydney Penrith NSW 1797 Australia

This paper studies the asymptotic behaviour of an M-estimator of regression parameters in the linear model when the design variables are either stationary short-range dependent (SRD), alpha-mixing or long-range dependent (LRD), and the errors are LRD. The weak consistency and the asymptotic distributions of the M-estimator are established. We present some simulated examples to illustrate the efficiency of the proposed M-estimation method.

关键词： alpha-mixing asymptotic normality consistency linear regression models long-range dependence M-estimation

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A NOTE ON AN INPUT CONTROL MODEL OF A PREDICTIVE regression INTERVAL

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 1994年第3期45卷 354-357页

作者： MEHREZ, A MYERS, BL BEN GURION UNIV NEGEV IL-84105 BEER SHEVAISRAEL

A well-known problem of prediction in linear regression models is to find a confidence interval for the random value of the dependent variable when the values of the independent variables are given. Such a situation may arise in economic quality control models when the independent variables are costly inputs and the dependent variable is some measure of quality or production. In such a circumstance, an important control objective may be to find values for the inputs that will maximize the lower limit of the prediction confidence interval for a fixed budget, or alternatively, to minimize the cost of the inputs for a fixed lower limit of the confidence interval. In this paper, we shall show that global optima can be found using known algorithms. The special case of simple linear regression is discussed and an illustrative example is provided.

关键词： CONFIDENCE INTERVALS linear regression models

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FILTERING AND DENOISING IN linear regression ANALYSIS

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FLUCTUATION AND NOISE LETTERS 2010年第4期9卷 343-358页

作者： Hassani, Hossein Mahmoudvand, Rahim Yarmohammadi, Masoud Stat Res & Training Ctr SRTC Tehran Iran Cardiff Univ Sch Math Stat Grp Cardiff CF24 4AG S Glam Wales Shahid Beheshti Univ Dept Stat Tehran *** Iran Payame Noor Univ Dept Stat Tehran Iran

In this paper we examine the effect of outlier/leverage point on the accuracy measures in the linear regression models. We use the coefficient of determination, which is a measure of model adequacy, to compare the effect of filtering approach on the least squares estimates. We also compare the performance of the filter-based approach with several resistant methods in a situation where there are several outliers in the data sets. Specifically, we examine the sensitivity of the resistant methods and the proposed approach in the circumstances where there are several leverage points in the data sets. To gain a better understanding of the effect of filtering and evaluating the performance of the proposed approach, we consider real data and simulation studies with several sample sizes, different percentage of outliers, and various noise levels.

关键词： linear regression models resistant methods singular spectrum analysis leverage point outlier

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Monitoring predictive and informative indicators of the energy status of dairy cows during early lactation in the context of monthly milk recordings using mid-infrared spectroscopy

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LIVESTOCK SCIENCE 2019年 221卷 6-14页

作者： Mueller, U. Kesser, J. Koch, C. Helfrich, H. -P. Rietz, C. Univ Bonn Inst Anim Sci Physiol & Hyg Unit Bonn Germany Hofgut Neumuehle Educ & Res Ctr Anim Husb Muenchweiler Germany Univ Bonn Inst Numer Simulat Bonn Germany Heidelberg Univ Mixed Methods Res Dept Educ Sci Heidelberg Germany

With the onset of lactation, voluntary feed intake does not increase as fast as the milk yield and the energy balance (EB) becomes physiologically negative. The risk of metabolic disorders increases with decreasing EB. During this time the concentration of beta-hydroxybutyrate (BHB) in serum increases. Herd managers cannot calculate the EB as the feed intake is commonly not quantified. Measuring the concentration of BHB in serum is generally not feasible on farms because blood samples must be collected and the respective analyses run. The motivation for developing the presented models was to be able to utilise the potential of the mid-infrared (MIR) spectroscopy spectral data (as part of the monthly milk recording)) for predicting the extensive energy status indicators EB and the BHB in serum in the first crucial lactation weeks (LW). In the first 10 LW, milk and blood samples were sampled from 65 primiparous (n = 20) and multiparous (n = 45) German Holstein cows. Milk samples were analysed by the laboratory of the milk recording organisation (MRO). For the reference data, blood samples were taken for BHB analysis and the EB of each cow was calculated using automatic weighing troughs for the energy intake. To predict the indicators of energy status, linear regression models that are easily applied in real-time were combined with milk spectral data, milk component data, and information on animal lactation number and stage. The linear regression model obtained better accuracy than the partial least square. In the first 4 LW the best linear regression model reached R-2 = 0.55 for EB in the multiparous cows (MC) and R-2 = 0.83 for EB in the primiparous cows (PC);the best model for the 5th to 10th LW reached R-2 = 0.57 for EB in the MC and R-2 = 0.71 for EB in the PC. To predict serum BHB in the first 4 LW the best linear regression model reached R-2 = 0.42. Sensitivity (sen) and specificity (spec) were calculated (cut-off values: BHB 1200 mu mol/L;EB 5% percentile). Cow

关键词： Energy balance beta-hydroxybutyrate in serum Monthly milk recording linear regression models

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Bayesian inference in spherical linear models: robustness and conjugate analysis

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JOURNAL OF MULTIVARIATE ANALYSIS 2006年第1期97卷 179-197页

作者： Arellano-Valle, RB del Pino, G Iglesias, P Pontificia Univ Catolica Chile Fac Matemat Santiago Chile

The early work of Zellner on the multivariate Student-t linear model has been extended to Bayesian inference for linear models with dependent non-normal error terms, particularly through various papers by Osiewalski, Steel and coworkers. This article provides a full Bayesian analysis for a spherical linear model. The density generator of the spherical distribution is here allowed to depend both on the precision parameter phi and on the regression coefficients beta. Another distinctive aspect of this paper is that proper priors for the precision parameter are discussed. The normal-chi-squared family of prior distributions is extended to a new class, which allows the posterior analysis to be carried out analytically. On the other hand, a direct joint modelling of the data vector and of the parameters leads to conjugate distributions for the regression and the precision parameters, both individually and jointly. It is shown that some model specifications lead to Bayes estimators that do not depend on the choice of the density generator, in agreement with previous results obtained in the literature under different assumptions. Finally, the distribution theory developed to tackle the main problem is useful on its own right. (c) 2005 Elsevier Inc. All rights reserved.

关键词： linear regression models elliptical and squared-radial distributions elliptical density generator dispersion and dispersion-location elliptical models Bayes estimator conjugate families

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Energy Efficient Dynamic Window Approach for Local Path Planning in Mobile Service Robotics

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IFAC-PapersOnLine 2016年第15期49卷 32-37页

作者： Henkel, Christian Bubeck, Alexander Xu, Weiliang Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart Germany Department of Mechanical Engineering University of Auckland Auckland New Zealand

An energy efficient local path planner for navigation of omnidirectional battery-powered mobile robots in dynamic environments is presented in this paper. The proposed algorithm extends the Dynamic Window Approach (DWA) to incorporate a cost function based on energy consumption. The estimated energy consumption during planning is predicted using a linear regression model that is learned on the fly. Empirical results are presented on a mobile robot platform that show a 9.79% decrease in energy consumption in comparison to the DWA approach. © 2016

关键词： Energy efficiency Cost functions Embedded systems Energy utilization Learning systems linear regression Mobile robots Motion planning Navigation Robot programming Battery powered Dynamic environments Dynamic window approach Energy efficient linear regression models Local path planning Mobile robot platforms Resource efficiencies

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Cis-regulation of IRF5 expression is unable to fully account for systemic lupus erythematosus association: analysis of multiple experiments with lymphoblastoid cell lines

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ARTHRITIS RESEARCH & THERAPY 2011年第3期13卷 1-12页

作者： Alonso-Perez, Elisa Suarez-Gestal, Marian Calaza, Manuel Kwan, Tony Majewski, Jacek Gomez-Reino, Juan J. Gonzalez, Antonio Hosp Clin Univ Santiago Inst Invest Sanitaria Lab Invest & Rheumatol Unit 10 E-15706 Santiago Spain McGill Univ Dept Human Genet Montreal PQ H3A 1B1 Canada Univ Santiago de Compostela Dept Med E-15782 Santiago De Compostela Spain

Introduction: Interferon regulatory factor 5 gene (IRF5) polymorphisms are strongly associated with several diseases, including systemic lupus erythematosus (SLE). The association includes risk and protective components. They could be due to combinations of functional polymorphisms and related to cis-regulation of IRF5 expression, but their mechanisms are still uncertain. We hypothesised that thorough testing of the relationships between IRF5 polymorphisms, expression data from multiple experiments and SLE-associated haplotypes might provide useful new information. Methods: Expression data from four published microarray hybridisation experiments with lymphoblastoid cell lines (57 to 181 cell lines) were retrieved. Genotypes of 109 IRF5 polymorphisms, including four known functional polymorphisms, were considered. The best linear regression models accounting for the IRF5 expression data were selected by using a forward entry procedure. SLE-associated IRF5 haplotypes were correlated with the expression data and with the best cis-regulatory models. Results: A large fraction of variability in IRF5 expression was accounted for by linear regression models with IRF5 polymorphisms, but at a different level in each expression data set. Also, the best models from each expression data set were different, although there was overlap between them. The SNP introducing an early polyadenylation signal, rs10954213, was included in the best models for two of the expression data sets and in good models for the other two data sets. The SLE risk haplotype was associated with high IRF5 expression in the four expression data sets. However, there was also a trend towards high IRF5 expression with some protective and neutral haplotypes, and the protective haplotypes were not associated with IRF5 expression. As a consequence, correlation between the cis-regulatory best models and SLE-associated haplotypes, regarding either the risk or protective component, was poor. Conclusions: Our analysis

关键词： systemic lupus erythematosus IRF5 lymphoblastoid cell lines cis-regulation disease susceptibility linear regression models

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