Add to ORKGthis paper. Procedures built by PolyAnalyst are treated as regression models which are nonlinear in general case. Specific methods of solution of associated nonlinear regression problems are described.<E-7> KEYWORDS: knowledge discovery, nonlinear regression, rational expressions 1. INTRODUCTION<E-38>
Linear regression models are useful for estimating statistical relationship between related variable...
Multiple regression provides the capability of using non-linear functions to fit various curvilinear...
The work covers the statistical experiments generated by the non-linear regression models. The iam i...
R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments f...
Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald ...
Linear and nonlinear methods for regression and classification and applications in
A new regularised least squares estimation algorithm is derived for the estimation of nonlinear dyna...
This book presents methods for investigating whether relationships are linear or nonlinear and for a...
Many real-life dependencies can be reasonably accurately described by linear functions. If we want a...
This thesis deals with solutions of nonlinear regression problems using R programming language. The ...
summary:New curvature measures for nonlinear regression models are developed and methods of their co...
Cluster structure in (multicollinear) data can be uti-lized by pattern recognition methods in order ...
Cluster structure in (multicollinear) data can be utilized by pattern recognition methods in order t...
Regression analysis is the most commonly used statistical method in the world. Although few would ch...
Linear regression analysis is one of the most important statistical methods. Itexamines the linear r...
Linear regression models are useful for estimating statistical relationship between related variable...
Multiple regression provides the capability of using non-linear functions to fit various curvilinear...
The work covers the statistical experiments generated by the non-linear regression models. The iam i...
R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments f...
Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald ...
Linear and nonlinear methods for regression and classification and applications in
A new regularised least squares estimation algorithm is derived for the estimation of nonlinear dyna...
This book presents methods for investigating whether relationships are linear or nonlinear and for a...
Many real-life dependencies can be reasonably accurately described by linear functions. If we want a...
This thesis deals with solutions of nonlinear regression problems using R programming language. The ...
summary:New curvature measures for nonlinear regression models are developed and methods of their co...
Cluster structure in (multicollinear) data can be uti-lized by pattern recognition methods in order ...
Cluster structure in (multicollinear) data can be utilized by pattern recognition methods in order t...
Regression analysis is the most commonly used statistical method in the world. Although few would ch...
Linear regression analysis is one of the most important statistical methods. Itexamines the linear r...
Linear regression models are useful for estimating statistical relationship between related variable...
Multiple regression provides the capability of using non-linear functions to fit various curvilinear...
The work covers the statistical experiments generated by the non-linear regression models. The iam i...