Method of Wavelength Selection for Partial Least Squares

The Analyst ◽  
1997 ◽  
Vol 122 (12) ◽  
pp. 1531-1537 ◽  
Author(s):  
Scott D. Osborne ◽  
Rainer Künnemeyer ◽  
Scott D. Osborne ◽  
Robert B. Jordan
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Wavelength Selection ◽  
Selection For

A weighted ensemble method based on wavelength selection for near-infrared spectroscopic calibration

2019 ◽  
Vol 11 (36) ◽  
pp. 4593-4599
Author(s):  
Shaohui Yu ◽  
Jing Liu
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Ensemble Method ◽  
Wavelength Selection ◽  
Weighted Clustering ◽  
Infrared Spectroscopic ◽  
Selection For ◽  
Pls Method

A weighted clustering and pruning of wavelength variables-partial least squares (WCPV-PLS) method was proposed.

Assessment of Partial Least-Squares Calibration and Wavelength Selection for Complex Near-Infrared Spectra

1998 ◽  
Vol 52 (6) ◽  
pp. 878-884 ◽  
Author(s):  
Michael J. McShane ◽  
Gerard L. Coté ◽  
Clifford H. Spiegelman
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Wavelength Selection ◽  
Absorption Bands ◽  
Full Spectrum ◽  
Single Spectrum ◽  
Near Infrared Spectra ◽  
Selection For

Complex near-infrared (near-IR) spectra of aqueous solutions containing five independently varying absorbing species were collected to assess the ability of partial least-squares (PLS) regression and wavelength selection for calibration and prediction of these species in the presence of each other. It was confirmed that PLS calibration models can successfully predict chemical concentrations of all five chemicals from a single spectrum. It was observed from the PLS spectral loadings that spectral regions containing absorption bands of a single analyte alone were not sufficient for the model to adequately predict the concentration of the analyte because of the high degree of overlap between glucose, lactate, ammonia, glutamate, and glutamine. Three wavelength selection algorithms were applied to the spectra to identify regions containing necessary information, and in each case it was found that nearly the entire spectral range was needed for each determination. The results suggest that wavelength selection does result in a reduction of data points from the full spectrum, but the decrease seen with these near-infrared spectra was less than typically seen in mid-IR or Raman spectra, where peaks are narrower and well separated. As a result of this need for more wavelengths, the engineering of a dedicated system to measure these analytes in complex media such as blood or tissue culture broths by using this near-infrared region (2.0–2.5 μm) is further complicated.

Automated wavelength selection for spectroscopic fuel models by symmetrically contracting repeated unmoving window partial least squares

2008 ◽  
Vol 92 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Jeffrey A. Cramer ◽  
Kirsten E. Kramer ◽  
Kevin J. Johnson ◽  
Robert E. Morris ◽  
Susan L. Rose-Pehrsson
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Wavelength Selection ◽  
Fuel Models ◽  
Selection For

Variable Selection for Partial Least-Squares Calibration of Near-Infrared Data from Orthogonally Designed Experiments

2002 ◽  
Vol 56 (3) ◽  
pp. 337-345 ◽  
Author(s):  
S. Kamaledin Setarehdan ◽  
John J. Soraghan ◽  
David Littlejohn ◽  
Daran A. Sadler
Keyword(s):  
Variable Selection ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Designed Experiments ◽  
Selection For ◽  
Infrared Data

Molecular spectroscopic wavelength selection using combined interval partial least squares and correlation coefficient optimization

2019 ◽  
Vol 11 (24) ◽  
pp. 3108-3116 ◽  
Author(s):  
Weiwei Jiang ◽  
Changhua Lu ◽  
Yujun Zhang ◽  
Wei Ju ◽  
Jizhou Wang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Correlation Coefficient ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Vital Role ◽  
Wavelength Selection ◽  
Coefficient Optimization

Wavelength selection plays a vital role in employing near-infrared spectroscopy for analyzing samples.

Feature Wavelength Selection of Phytoplankton Fluorescence Spectra Based on Partial Least Squares

2014 ◽  
Vol 34 (9) ◽  
pp. 0930002
Author(s):  
余晓娅 Yu Xiaoya ◽  
张玉钧 Zhang Yujun ◽  
殷高方 Yin Gaofang ◽  
肖雪 Xiao Xue ◽  
赵南京 Zhao Nanjing ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Fluorescence Spectra ◽  
Wavelength Selection ◽  
Selection Of

Correlation coefficient optimization in partial least-squares regression with application to ATR-FTIR spectroscopic analysis

2015 ◽  
Vol 7 (14) ◽  
pp. 5780-5786 ◽  
Author(s):  
Yifang Chen ◽  
Jiemei Chen ◽  
Tao Pan ◽  
Yun Han ◽  
Lijun Yao
Keyword(s):  
Human Serum ◽  
Least Squares ◽  
Partial Least Squares ◽  
Correlation Coefficient ◽  
Partial Least Squares Regression ◽  
Spectroscopic Analysis ◽  
Selection Method ◽  
Least Squares Regression ◽  
Wavelength Selection ◽  
Coefficient Optimization

A wavelength selection method for spectroscopic analysis, named correlation coefficient optimization partial least-squares (CCO-PLS), is proposed, and was successfully employed for reagent-free ATR-FTIR spectroscopic analysis of albumin and globulin in human serum.

scholarly journals Quantitative determination of naltrexone by attenuated total reflectance – FTIR spectrometry using partial least squares (PLS) wavelength selection

2009 ◽  
Vol 23 (2) ◽  
pp. 113-121 ◽  
Author(s):  
Mohammadreza Khanmohammadi ◽  
Hamid Mobedi ◽  
Elaheh Mobedi ◽  
Kazem Kargosha ◽  
Amir Bagheri Garmarudi ◽  
...  
Keyword(s):  
Quantitative Determination ◽  
Least Squares ◽  
Partial Least Squares ◽  
Reference Method ◽  
Attenuated Total Reflectance ◽  
Infrared Spectrometry ◽  
Wavelength Selection ◽  
Statistical Parameters ◽  
Total Reflectance

A new method is presented for quantitative determination of naltrexone in aqueous solutions based up on the wavelength selection in mid-FTIR spectra using partial least squares (PLS) technique. The main aim is to find wavelengths which produce significant improvements in PLS prediction. PLS wavelength selection treatment is performed on the data obtained by attenuated total reflectance Fourier transform infrared spectrometry in 830–1800 cm−1wavenumber range. No separation or extraction steps are required prior to determination procedure and a simple pretreatment is performed. Absorbance spectra were employed for measurements using a set of 7 aqueous standard solutions of naltrexone. The method is applicable for pharmaceutical samples in aqueous solution in the presence of impurities, while it is simple, rapid and accurate. The results obtained from real samples were compared with those obtained using Ultra Violet spectrophotometry as a reference method. Statistical parameters such as R2, REP, RMSEC and RMSECV were evaluated, and number of factors, number of scans and resolution were also optimized. In this method R2and RMSEC for proposed procedure have been found to be 0.9983 and 0.1297, respectively.

APPI(+)-FTICR mass spectrometry coupled to partial least squares with genetic algorithm variable selection for prediction of API gravity and CCR of crude oil and vacuum residues

Fuel ◽  
2017 ◽  
Vol 193 ◽  
pp. 39-44 ◽  
Author(s):  
Diana Catalina Palacio Lozano ◽  
Jorge Armando Orrego-Ruiz ◽  
Rafael Cabanzo Hernández ◽  
Jáder Enrique Guerrero ◽  
Enrique Mejía-Ospino
Keyword(s):  
Mass Spectrometry ◽  
Genetic Algorithm ◽  
Variable Selection ◽  
Crude Oil ◽  
Least Squares ◽  
Partial Least Squares ◽  
Fticr Mass Spectrometry ◽  
Selection For
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