Interval estimation in multivariate curve resolution by exploiting the principles of error propagation in linear least squares

[1]  Jahan B. Ghasemi,et al.  Receptor modeling of environmental aerosol data using MLPCA-MCR-ALS , 2017 .

[2]  S. Rutan,et al.  Analysis of Liquid Chromatography-Mass Spectrometry Data with an Elastic Net Multivariate Curve Resolution Strategy for Sparse Spectral Recovery. , 2017, Analytical chemistry.

[3]  R. Tauler,et al.  Error propagation along the different regions of multivariate curve resolution feasible solutions , 2017 .

[4]  Eun Sug Park,et al.  Bayesian quantile multivariate receptor modeling , 2016 .

[5]  Romà Tauler,et al.  Chemometric analysis of comprehensive LC×LC-MS data: Resolution of triacylglycerol structural isomers in corn oil. , 2016, Talanta.

[6]  D. Brie,et al.  Bayesian Positive Source Separation for Spectral Mixture Analysis , 2016 .

[7]  Eun Sug Park,et al.  Robust Bayesian multivariate receptor modeling , 2015 .

[8]  Romà Tauler,et al.  Vibrational spectroscopic image analysis of biological material using multivariate curve resolution–alternating least squares (MCR-ALS) , 2015, Nature Protocols.

[9]  Romà Tauler,et al.  Sensitivity equation for quantitative analysis with multivariate curve resolution-alternating least-squares: theoretical and experimental approach. , 2012, Analytical chemistry.

[10]  M. Jalali-Heravi,et al.  Chromatographic fingerprint analysis of secondary metabolites in citrus fruits peels using gas chromatography-mass spectrometry combined with advanced chemometric methods. , 2012, Journal of chromatography. A.

[11]  Hadi Parastar,et al.  Resolution and quantification of complex mixtures of polycyclic aromatic hydrocarbons in heavy fuel oil sample by means of GC × GC-TOFMS combined to multivariate curve resolution. , 2011, Analytical chemistry.

[12]  R. Tauler,et al.  Uniqueness and rotation ambiguities in Multivariate Curve Resolution methods , 2011 .

[13]  Marcel Maeder,et al.  Resolution of rotational ambiguity for three-component systems. , 2011, Analytical chemistry.

[14]  Romà Tauler,et al.  MCR-BANDS: A user friendly MATLAB program for the evaluation of rotation ambiguities in Multivariate Curve Resolution , 2010 .

[15]  Peter D. Wentzell,et al.  Comparison of the results obtained by four receptor modelling methods in aerosol source apportionment studies , 2009 .

[16]  Eun Sug Park,et al.  A computation saving jackknife approach to receptor model uncertainty statements for serially correlated data , 2007 .

[17]  M. Bosco,et al.  PARAFAC and MCR-ALS applied to the quantitative monitoring of the photodegradation process of polycyclic aromatic hydrocarbons using three-dimensional excitation emission fluorescent spectra Comparative results with HPLC. , 2007, Talanta.

[18]  M. Viana,et al.  Identification of PM sources by principal component analysis (PCA) coupled with wind direction data. , 2006, Chemosphere.

[19]  Margaret Werner-Washburne,et al.  BMC Bioinformatics BioMed Central Methodology article Multivariate curve resolution of time course microarray data , 2006 .

[20]  Romà Tauler,et al.  On rotational ambiguity in model‐free analyses of multivariate data , 2006 .

[21]  Romà Tauler,et al.  State of the art in methods and software for the identification, resolution and apportionment of contamination sources , 2006 .

[22]  R. Tauler,et al.  Noise propagation and error estimations in multivariate curve resolution alternating least squares using resampling methods , 2004 .

[23]  Ronald C. Henry,et al.  Bilinear estimation of pollution source profiles and amounts by using multivariate receptor models , 2002 .

[24]  Peter Guttorp,et al.  Multivariate receptor models and model uncertainty , 2002 .

[25]  Sylvia Richardson,et al.  Markov Chain Monte Carlo in Practice , 1997 .

[26]  R. Tauler Multivariate curve resolution applied to second order data , 1995 .

[27]  W. Windig Self-modeling mixture analysis of spectral data with continuous concentration profiles , 1992 .

[28]  Bruce R. Kowalski,et al.  An extension of the multivariate component-resolution method to three components , 1985 .

[29]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .