نتایج جستجو برای: nonlinear least squares regression
تعداد نتایج: 888904 فیلتر نتایج به سال:
Abstract. For the given data (wi, xi, yi), i = 1, . . . , n, and the given model function f(x;θ), where θ is a vector of unknown parameters, the goal of regression analysis is to obtain estimator θ∗ of the unknown parameters θ such that the vector of residuals is minimized in some sense. The common approach to this problem of minimization is the least-squares method, that is minimizing the L2 n...
This paper presents regression models obtained from a process of blind prediction of peptide binding affinity from provided descriptors for several distinct datasets as part of the 2006 Comparative Evaluation of Prediction Algorithms (COEPRA) contest. This paper finds that kernel partial least squares, a nonlinear partial least squares (PLS) algorithm, outperforms PLS, and that the incorporatio...
Partial Least Squares (PLS) is an efficient multivariate statistical regression technique that has proven to be particularly useful for analysis of highly collinear data. To predict response variables Y from independent variables X, PLS attempts to find a set of common orthogonal latent variables by projecting both X and Y onto a new subspace respectively. As an increasing interest in multiway ...
We consider best approximation problems in a nonlinear subset ℳ of Banach space functions (
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