Results 1 to 10 of about 4,421,578 (317)
, 2021 Regression analysis between mutation rate, effective population size (Ne), and genome ...
Xiaojun Wang (9353387)
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Inverted Weibull Regression Models and Their Applications
, 2021 In this paper, we propose the classical and Bayesian regression models for use in conjunction with the inverted Weibull (IW) distribution; there are the inverted Weibull Regression model (IW-Reg) and inverted Weibull Bayesian regression model (IW-BReg ...
Sarah R. Al-Dawsari, Khalaf S. Sultan
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Likelihood-based Imprecise Regression [PDF]
, 2011 We introduce a new approach to regression with imprecisely observed data, combining likelihood inference with ideas from imprecise probability theory, and thereby taking different kinds of uncertainty into account.
Marco E. G. V. Cattaneo +4 more
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, 2016 This study aims to compare the different between two data sets that having the relationship between the dependent and independent variables at each quantile using testing the equality of two parametric quantile regression functions, the conditional ...
Tonggumnead, Unchalee; Faculty of Science and Technology, Rajamangala University of Technology Thanyaburi, 39 Moo1, Rangsit-Nakhonnayok Rd. Klong6, Thanyaburi, Pathum Thani 12110Thailand
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, 2018 Files used for regression analyses reported in SM Table S1 of Engelmann, Meyer, Ruff ...
Jan Engelmann (529569)
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COMPARATION ON SEVERAL SMOOTHING METHODS IN NONPARAMETRIC REGRESSION [PDF]
, 2011 There are three nonparametric regression methods covered in this section. These are Moving Average Filtering-Based Smoothing, Local Regression Smoothing, and Kernel Smoothing Methods.
Isnanto, R.Rizal, Rizal Isnanto, R
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Penalized wavelet monotone regression [PDF]
, 2007 In this paper we focus on nonparametric estimation of a constrained regression function using penalized wavelet regression techniques. This results into a convex op- timization problem under linear constraints.
Irène Gijbels +5 more
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jkleinj/regression: regression demo
, 2017 R demo scripts for linear regression and ...
Jens Kleinjung
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Regression-Assisted Deconvolution
, 2018 We present a semi-parametric deconvolution estimator for the density function of a random variable X that is measured with error. Traditional deconvolution estimators rely only on assumptions about the distribution of X and the error in its measurement ...
Leonard A. Stefanski (2569393) +1 more
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Comparison of regression models under multi-collinearity
, 2018 Multicollinearity is a major problem in linear regression analysis and several methods exists in the literature to deal with the same. Ridge regression is one of the most popular methods to overcome the problem followed by Generalized Ridge Regression ...
Srinivasan, Rangasami M.; Department of Statistics, University of Madras +2 more
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