نتایج جستجو برای: principal component Regression

تعداد نتایج: 998116  

Journal: :Communications for Statistical Applications and Methods 2015

Journal: :iranian journal of pharmaceutical sciences 0
kinjal r patel shri bm shah college of pharmaceutical education and research, college campus, modasa, 383315, gujarat, india. laxman m prajapati shri bm shah college of pharmaceutical education and research, college campus, modasa, 383315, gujarat, india. amit k joshi shri bm shah college of pharmaceutical education and research, college campus, modasa, 383315, gujarat, india. mahammadali l kharodiya shri bm shah college of pharmaceutical education and research, college campus, modasa, 383315, gujarat, india. jimish r patel shri bm shah college of pharmaceutical education and research, college campus, modasa, 383315, gujarat, india.

chemometric techniques in spectral analysis have gained importance in the quality control of  the drugs mixtures and pharmaceutical formulations containing two or more drugs with overlapping spectra. since theophylline and etophylline have common chromophore, they cannot be analyzed simultaneously using conventional uv methods. simultaneous spectrophotometric determination of etophylline and th...

Journal: :Statistical Analysis and Data Mining: The ASA Data Science Journal 2018

Journal: :Canadian Journal of Statistics 2021

Journal: :SIAM Journal on Matrix Analysis and Applications 2019

2001
P. Filzmoser

In this note we introduce a method for robust principal component regression. Robust principal components are computed from the predictor variables, and they are used afterwards for estimating a response variable by performing robust linear multiple regression. The performance of the method is evaluated at a test data set from geochemistry. Then it is used for the prediction of censored values ...

Journal: :Journal of the American Statistical Association 2021

Principal component regression (PCR) is a simple, but powerful and ubiquitously utilized method. Its effectiveness well established when the covariates exhibit low-rank structure. However, its ability to handle settings with noisy, missing, mixed-valued, that is, discrete continuous, not understood remains an important open challenge. As main contribution of this work, we establish robustness P...

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