MULTIVARIATE CURVE RESOLUTION, BRINGING AND EXTRACTING SCIENTIFIC KNOWLEDGE FROM THE DATA ANALYSIS

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DE JUAN ANNA; JAUMOT JOAQUIN; GARGALLO RAIMUNDO; TAULER ROMA

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Seminar Paper

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Seminar: IRANIAN BIENNIAL CHEMOMETRICS SEMINAR
Year:2011 | Issue:3

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Title

MULTIVARIATE CURVE RESOLUTION, BRINGING AND EXTRACTING SCIENTIFIC KNOWLEDGE FROM THE DATA ANALYSIS

Author(s)

DE JUAN ANNA | JAUMOT JOAQUIN | GARGALLO RAIMUNDO | TAULER ROMA | Issue Writer Certificate

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Abstract

MULTIVARIATE CURVE RESOLUTION METHODS AIM AT PROVIDING A SCIENTIFIC MEANINGFUL DESCRIPTION OF THE VARIATION IN THE DATA SETS THROUGH A SMALL BILINEAR MODEL OF BASIC AND INTERPRETABLE CONTRIBUTIONS.THE MOST DISTINCT CHARACTERISTIC OF MCR METHODS IS THE STRAIGHT SCIENTIFIC MEANING OF THE RESULTS OBTAINED, WHICH IS A DIRECT CONSEQUENCE OF THE POSSIBILITY TO INTRODUCE CHEMICAL/SCIENTIFIC INFORMATION ABOUT THE PROPERTIES OF THE BASIC CONTRIBUTIONS SOUGHT (INSTRUMENTAL RESPONSES, CONCENTRATION PROFILES, ENVIRONMENTAL OR BIOLOGICAL PATTERNS, …) UNDER THE FORM OF CONSTRAINTS.ANOTHER RELEVANT ASPECT LINKED TO MCR IS THE POSSIBILITY TO WORK WITH MULTISET STRUCTURES THAT MAY ENCLOSE DATA COMING FROM DIFFERENT EXPERIMENTS, TECHNIQUES OR, IN A MORE GENERAL SENSE, COLLECTED UNDER DIFFERENT CONDITIONS OR IN DIFFERENT SCENARIOS. THIS APPROACH PROVIDES A MORE INTEGRAL AND RUGGED DESCRIPTION OF THE PROBLEM UNDER STUDY DUE TO THE ACTIVE USE OF MORE DIVERSE INPUT INFORMATION AND TO THE PARTICULAR PROPERTIES OF MULTISET STRUCTURES. SUCH AN ASPECT IS VERY RELEVANT IN AREAS, SUCH AS PROCESS ANALYSIS.THE UNDERLYING MCR BILINEAR MODEL OFFERS CERTAIN ADVANTAGES. ON THE ONE HAND, THE MATRICES OF BASIC CONTRIBUTIONS CAN BE USED AS EXCELLENT MEANINGFUL COMPRESSIONS OF THE RAW DATA SET FOR OTHER DATA ANALYSIS PURPOSES, E.G. IN THE CASE OF HYPERSPECTRAL IMAGES. ON THE OTHER HAND, THE SIMPLICITY AND INTERPRETABILITY OF THE MCR RESULTS MAKE THIS METHOD AN EXCELLENT OPTION TO EXPLORE DATA SETS WELL BEYOND THE TYPICAL ANALYTICAL FIELD, SUCH AS ENVIRONMENTAL OR -OMIC MEASUREMENTS.THIS WORK WILL GIVE AN OVERVIEW OF THE MAIN ASPECTS MENTIONED ABOVE, STRESSING BRIEFLY THE KIND OF DATA SETS AND INFORMATION THAT CAN BE USED WHEN APPLYING MCR METHODS AND ILLUSTRATING THE POWER OF THE METHOD WITH EXAMPLES FROM DIVERSE SCIENTIFIC FIELDS.

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APA: Copy

DE JUAN, ANNA, JAUMOT, JOAQUIN, GARGALLO, RAIMUNDO, & TAULER, ROMA. (2011). MULTIVARIATE CURVE RESOLUTION, BRINGING AND EXTRACTING SCIENTIFIC KNOWLEDGE FROM THE DATA ANALYSIS. IRANIAN BIENNIAL CHEMOMETRICS SEMINAR. SID. https://sid.ir/paper/909320/en

Vancouver: Copy

DE JUAN ANNA, JAUMOT JOAQUIN, GARGALLO RAIMUNDO, TAULER ROMA. MULTIVARIATE CURVE RESOLUTION, BRINGING AND EXTRACTING SCIENTIFIC KNOWLEDGE FROM THE DATA ANALYSIS. 2011. Available from: https://sid.ir/paper/909320/en

IEEE: Copy

ANNA DE JUAN, JOAQUIN JAUMOT, RAIMUNDO GARGALLO, and ROMA TAULER, “MULTIVARIATE CURVE RESOLUTION, BRINGING AND EXTRACTING SCIENTIFIC KNOWLEDGE FROM THE DATA ANALYSIS,” presented at the IRANIAN BIENNIAL CHEMOMETRICS SEMINAR. 2011, [Online]. Available: https://sid.ir/paper/909320/en

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