Results 11 to 20 of about 1,145,773 (286)
Southwest Respiratory and Critical Care Chronicles, 2014 Gilbert Berdine, Shengping Yang
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A mixture of linear-linear regression models for a linear-circular regression [PDF]
Statistical Modelling, 2019 We introduce a new approach to a linear-circular regression problem that relates multiple linear predictors to a circular response. We follow a modelling approach of a wrapped normal distribution that describes angular variables and angular distributions and advances them for a linear-circular regression analysis.
Chiwoo Park, Ali Esmaieeli Sikaroudi
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Linearized binary regression [PDF]
2018 52nd Annual Conference on Information Sciences and Systems (CISS), 2018 Probit regression was first proposed by Bliss in 1934 to study mortality rates of insects. Since then, an extensive body of work has analyzed and used probit or related binary regression methods (such as logistic regression) in numerous applications and fields.
Andrew S. Lan +2 more
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Linear regression in genetic association studies. [PDF]
PLoS ONE, 2013 In genomic research phenotype transformations are commonly used as a straightforward way to reach normality of the model outcome. Many researchers still believe it to be necessary for proper inference. Using regression simulations, we show that phenotype
Petra Bůžková
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MODELING CLUSTERWISE LINEAR REGRESSION ON POVERTY RATE IN INDONESIA
Barekeng, 2023 When a person's income is so low that it cannot cover even the most basic living expenses, they are said to be poor. Data on poverty levels and hypothesized causes are used in this study. If the data pattern forms clusters, one of the regression analyses
Eni Meylisah +4 more
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Shrinkage Estimators for the Intercept in Linear and Uplift Regression
Scientific Annals of Computer Science, 2023 Shrinkage estimators modify classical statistical estimators by scaling them towards zero in order to decrease their prediction error. We propose shrinkage estimators for linear regression models which explicitly take into account the presence ...
Szymon Jaroszewicz, Krzysztof Rudas
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Linear Regression Based Real-Time Filtering
Advances in Electrical and Electronic Engineering, 2013 This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications.
Misel Batmend, Daniela Perdukova
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Robust Model Selection in Linear regression [PDF]
Kirkuk Journal of Science, 2007 The research deals with the proposing of robust formula for the accumulate prediction error (APE) criterion which is used in selecting regression model. The proposed formula evaluated with a simulation study.
Dr. Sabah Haseeb Hassan
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Research on linear regression algorithm [PDF]
MATEC Web of ConferencesLinear regression is one of the most widely used predictive models in statistics and machine learning. This paper aims to comprehensively discuss the theoretical basis, mathematical principle and application of linear regression algorithm in various ...
Qu Kecheng
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Linear Regression for Heavy Tails
Risks, 2018 There exist several estimators of the regression line in the simple linear regression: Least Squares, Least Absolute Deviation, Right Median, Theil–Sen, Weighted Balance, and Least Trimmed Squares.
Guus Balkema, Paul Embrechts
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