✦ LIBER ✦

Prediction error in least squares regression: Further critique on the deviation used in The Unscrambler

✍ Scribed by Klaas Faber; Bruce R. Kowalski

Publisher: Elsevier Science
Year: 1996
Tongue: English
Weight: 772 KB
Volume: 34
Category: Article
ISSN: 0169-7439
DOI: 10.1016/0169-7439(96)00022-6

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Prediction error in partial least square

Prediction error in partial least squares regression: a critique on the deviation used in The Unscrambler

✍ S. De Vries; Cajo J.F. Ter Braak 📂 Article 📅 1995 🏛 Elsevier Science 🌐 English ⚖ 498 KB

Choosing the number of factors in partia

Choosing the number of factors in partial least squares regression: estimating and minimizing the mean squared error of prediction

✍ Michael C. Denham 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 74 KB 👁 2 views

On the exponential rate of convergence o

On the exponential rate of convergence of the least squares estimator in the nonlinear regression model with Gaussian errors

✍ B.L.S. Prakasa Rao 📂 Article 📅 1984 🏛 Elsevier Science 🌐 English ⚖ 153 KB

The influence of weight with assay error

The influence of weight with assay error on gentamicin pharmacokinetics using the Bayesian and nonlinear least square regression analysis in appendicitis patients

✍ Jin Pil Burm 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 85 KB 👁 2 views

Parametric (modified least squares) and

Parametric (modified least squares) and non-parametric (Theil–Sen) linear regressions for predicting biophysical parameters in the presence of measurement errors

✍ Richard Fernandes; Sylvain G. Leblanc 📂 Article 📅 2005 🏛 Elsevier Science 🌐 English ⚖ 469 KB

Remote sensing often involves the estimation of in situ quantities from remote measurements. Linear regression, where there are no nonlinear combinations of regressors, is a common approach to this prediction problem in the remote sensing community. A review of recent remote sensing articles using u

Comparative prediction of the retention

Comparative prediction of the retention behaviour of small peptides in several reversed-phase high-performance liquid chromatography columns by using partial least squares and multiple linear regression

✍ V. Casal; P.J. Martin-Alvarez; T. Herraiz 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 550 KB

The retention behaviour of small standard peptides in reversed-phase high-performance liquid chromatography (RP-HPLC) is evaluated. Chromatographic retention of small peptides highly correlates with the summing of the hydrophobic contributions of their respective amino acid residues. Prediction of p