Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Calibration Curves: Linear Least Squares

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...

Instrument Calibration

Instrument Calibration

Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Design Aspects of Scheffe's Calibration Theory Using Linear Splines.

Journal of research of the National Bureau of Standards (1977)·2021

Same author

Enzyme functionalized microgels enable precise regulation of dissolved oxygen and anaerobe culture.

Materials today. Bio·2021

Same author

In vivo optoacoustic temperature imaging for image-guided cryotherapy of prostate cancer.

Physics in medicine and biology·2018

Same author

Molecular characterization of environmental Cladosporium species isolated from Iran.

Current medical mycology·2018

Same author

Proteolytic activity and cooperative hemolytic effect of dermatophytes with different species of bacteria.

Current medical mycology·2017

Same author

Molecular identification and <i>in-vitro</i> antifungal susceptibility testing of <i>Candida</i> species isolated from patients with onychomycosis.

Current medical mycology·2017

Search research articles

Related Experiment Video

Updated: Jun 1, 2026

High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis

High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis

Published on: December 22, 2015

Theoretical Justification of Wavelength Selection in PLS Calibration: Development of a New Algorithm.

C H Spiegelman¹, M J McShane, M J Goetz

¹Department of Statistics and Biomedical Engineering Program, Texas A&M University, College Station, Texas 77845, and Biomedical Engineering Center, Laser & Spectroscopy Program, University of Texas Medical Branch, Galveston, Texas 77550.

Analytical Chemistry

|June 8, 2011

Summary

Selecting informative variables improves partial least-squares calibration by reducing bias. A new method incorporating spectral residuals enhances selection accuracy, especially with noisy data exhibiting outliers.

More Related Videos

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Fabrication And Characterization Of Photonic Crystal Slow Light Waveguides And Cavities

Fabrication And Characterization Of Photonic Crystal Slow Light Waveguides And Cavities

Published on: November 30, 2012

Related Experiment Videos

Last Updated: Jun 1, 2026

High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis

High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis

Published on: December 22, 2015

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Fabrication And Characterization Of Photonic Crystal Slow Light Waveguides And Cavities

Fabrication And Characterization Of Photonic Crystal Slow Light Waveguides And Cavities

Published on: November 30, 2012

Area of Science:

Chemometrics
Spectroscopy
Data Analysis

Background:

Partial least-squares (PLS) calibration is widely used for spectral data analysis.
Variable selection is crucial for optimizing PLS model performance.
Uninformative variables can introduce bias and reduce prediction accuracy in PLS models.

Purpose of the Study:

To investigate the mathematical basis for improving PLS calibration through informative variable selection.
To compare a novel variable selection method incorporating spectral residuals against a traditional approach.
To evaluate the impact of different noise distributions on variable selection efficacy.

Main Methods:

Theoretical analysis of calibration slopes to understand bias introduced by uninformative wavelengths.
Development and application of a new variable selection method that includes spectral residual estimates.
Testing of three datasets: simulated data with added Gaussian/log-normal noise, near-infrared spectra of glucose, and Raman spectra of glucose.

Main Results:

Theoretical analysis confirmed that uninformative wavelengths negatively impact PLS calibrations by introducing bias.
Variable selection consistently improved prediction accuracy across all tested datasets.
The new method, incorporating spectral residuals, demonstrated superior performance for data with noise distributions leading to significant outliers.

Conclusions:

The selection of informative variables is essential for robust PLS calibration.
Variable selection algorithm design should account for spectral noise distributions to enhance performance.
The proposed method offers improved selection, particularly for datasets prone to outliers.