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Nonlinear regression
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#	Item
111	International Journal of © International Science Press 1(1) June 2010, pp[removed]SYSTEMS AND SYNTHETIC BIOLOGY Add to Reading List Source URL: bioenergycenter.org Language: English - Date: 2011-04-12 13:17:22 Linear regression Mathematical and theoretical biology Lotka–Volterra equation Mathematical model Nonlinear system Differential equation Estimation theory Nonlinear regression Parameter Statistics Regression analysis Econometrics
112	Subscriber access provided by INST ADV STUDIES BASIC SCI Article An Improved Approximation to the Estimation of the Critical F Values in Best Subset Regression Add to Reading List Source URL: www.iasbs.ac.ir Language: English - Date: 2009-02-08 14:33:12 Model selection Statistical tests Statistical methods Stepwise regression Nonlinear regression Linear regression Feature selection Least squares Multivariate normal distribution Statistics Regression analysis Econometrics
113	Automated piecewise power-law modeling of biological systems Add to Reading List Source URL: bioenergycenter.org Language: English - Date: 2010-03-03 10:14:54 Piecewise linear function Nonlinear regression Piecewise linear Linear regression Power law Piecewise Artificial neuron Least squares Local regression Statistics Regression analysis Mathematical analysis
114	Comparing basal area growth models, consistency of parameters, and accuracy of prediction J. J. Colberta, Michael Schuckersb, and Desta Fekedulegnb a b Add to Reading List Source URL: www.iemss.org Language: English - Date: 2011-11-23 04:44:30 Estimation theory Parametric statistics Statistical methods Linear regression Mathematical model Economic model Nonlinear regression F-test Linear model Statistics Regression analysis Econometrics
115	Autonomous Helicopter Control Using Fuzzy Gain Scheduling Add to Reading List Source URL: www.ida.liu.se Language: English - Date: 2012-02-01 04:09:11 Fuzzy logic Control engineering Dynamical systems Control theory Regression analysis X Window System Fuzzy control system Control system Nonlinear system Systems theory Science Software
116	NISS Secure Analysis of Distributed Chemical Databases without Data Integration Alan F. Karr, Jun Feng, Xiaodong Lin, Jerome P. Reiter, Ashish P. Sanil and Add to Reading List Source URL: www.niss.org Language: English - Date: 2005-06-24 12:21:50 Least squares Estimation theory Parametric statistics Linear regression Coefficient of determination Errors and residuals in statistics Nonlinear regression Durbin–Watson statistic Statistics Regression analysis Econometrics
117	NISS Secure Statistical Analysis of Distributed Databases Alan F. Karr, Xiaodong Lin, Ashish P. Sanil, Jerome P. Reiter Add to Reading List Source URL: www.niss.org Language: English - Date: 2005-07-05 12:58:10 Coefficient of determination Least squares Linear discriminant analysis Gauss–Markov theorem Nonlinear regression Bayesian linear regression Statistics Regression analysis Linear regression
118	Environmental Modelling & Software[removed]899e913 www.elsevier.com/locate/envsoft PEAS: A toolbox to assess the accuracy of estimated parameters in environmental models Nicola Checchi, Elisabetta Giusti, Stefano Marsi Add to Reading List Source URL: www.dsi.unifi.it Language: English - Date: 2009-12-17 04:55:04 Scientific modeling Statistical inference Estimation theory Sensitivity analysis Linear regression Computer simulation Confidence interval Nonlinear regression Maximum likelihood Statistics Econometrics Regression analysis
119	Length-Weight Relationships for Six Species of Billfishes in the Central Pacific Ocean ROBERT A. SKILLMAN and MARIAN Y.Y. YONGl ABSTRACT Weight-length relationships for six species of billfishes in the central Pacific Oc Add to Reading List Source URL: www.pifsc.noaa.gov Language: English - Date: 2009-03-18 14:11:37 Istiophoridae Least squares Econometrics Sport fish Trolling Marlin Linear regression Nonlinear regression Ordinary least squares Statistics Regression analysis Fish
120	Cottingham – Web-only material Appendix 1. The matrix formulation for regression and ANOVA (Neter et al[removed]Both regression and ANOVA can be described using the general linear model Y = X + , where Add to Reading List Source URL: www.indiana.edu Language: English - Date: 2014-10-25 14:57:21 Linear regression General linear model Degrees of freedom Errors and residuals in statistics Nonlinear regression Simple linear regression Effect size Ordinary least squares Dummy variable Statistics Regression analysis Analysis of variance

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