Change-point Estimation in A Segmented Linear Regression Via Empirical Likelihood[J].Communications in Statistics-Simulation and Computation,2010,(39).Z. Liu and L. Qian, "Changepoint Estimation in a Seg- mented Linear Regression via Empirical Likelihood," Communications in Statistics--Simulation and...
F.Estimation of the linear-linear segmented regression model in the presence of measurement error. Commun.Stat. Theory Meth ods . 1985Gbur, E. E., & Dahm, P. F. (1985). Estimation of the linear-linear segmented regression model in the presence of measurement error. Communications in ...
All analyses were performed in the R programming environment, with age, height, and weight identified as key predictors. 4.1. Statistical Analyses Two primary statistical models were compared: GAMLSS and segmented linear regression. For prediction accuracy, K-fold cross-validation (with 10 folds) was...
TitleSegmentedrelationshipsinregressionmodels Version0.2-8.2 Date2011-07-05 AuthorVitoM.R.Muggeo MaintainerVitoM.R.Muggeo DescriptionGivena(generalized)linearmodel,seg- mented‘updates’themodelbyaddingoneormoresegmentedrelationships. Severalvariableswithmultiplebreakpointsareallowed. LicenseGPL RepositoryCRAN Date...
In the 1970s, an equation that allows estimation of df values when the contact angle between the liquid and the tube walls is zero, leading to low df values, was proposed [15]: (5.3)df=0.67πd(μv/γ)2/3where μ is the linear velocity of the segmented stream; ν is the liquid ...
M. (1987) The application of the annealing algorithm to the construction of exact optimal designs for linear-regression models.Technometrics,29, 439–447. Google Scholar Johnson, D. S., Aragon, C. R., McGeoch, L. A. and Schevon, C. (1989) Optimization by simulated annealing: an ...
Linear and nonlinear modeling of antifungal activity of some heterocyclic ring derivatives using multiple linear regression and Bayesian-regularized neural net- works. J Mol Model. 2006;12:168–81. https://doi.org/10.1007/ s00894-005-0014-x. 41. Wu D, Huang H,...
Logistic regression After manual annotation of a training set and feature extraction, a supervised machine learning algorithm was introduced to perform the segmentation assessment. Logistic regression is a form of generalized linear model that models the posterior probability of a dichotomous or continuous...
These newly proposed AA indices were used in QSAR study of two dipeptide data sets; 58 ACE inhibitors, and 48 BTT. The linear relationships between the proposed indices and the biological activities of the dipeptides were modeled using principal component regression (PCR) and partial least square ...
Logistic regression After manual annotation of a training set and feature extraction, a supervised machine learning algorithm was introduced to perform the segmentation assessment. Logistic regression is a form of generalized linear model that models the posterior probability of a dichotomous or continuous...