Determination of the Number of Significant Components in Liquid Chromatography Nuclear Magnetic Resonance Spectroscopy
暂无分享,去创建一个
[1] Klaas Faber,et al. Critical evaluation of two F-tests for selecting the number of factors in abstract factor analysis , 1997 .
[2] R. Brereton,et al. Resolution of LC/1H NMR data applied to a three‐component mixture of polyaromatic hydrocarbons , 2002 .
[3] Johanna Smeyers-Verbeke,et al. Handbook of Chemometrics and Qualimetrics: Part A , 1997 .
[4] Window evolving factor analysis for assessment of peak homogeneity in liquid chromatography , 1993 .
[5] D. L. Massart,et al. Eigenstructure tracking analysis for assessment of peak purity in high-performance liquid chromatography with diode array detection , 1995 .
[6] Richard G. Brereton,et al. A comparison of deconvolution methods as applied to high performance liquid chromatography-diode array detector-electrospray mass spectrometry of 2- and 3-hydroxypyridine at varying pH in the presence of severely tailing peak shapes , 1999 .
[7] Edmund R. Malinowski,et al. Statistical F‐tests for abstract factor analysis and target testing , 1989 .
[8] J. Gani,et al. Perspectives in Probability and Statistics. , 1980 .
[9] Richard G. Brereton,et al. Chemometrics: Data Analysis for the Laboratory and Chemical Plant , 2003 .
[10] H. R. Keller,et al. Peak purity control in liquid chromatography with photodiode-array detection by a fixed size moving window evolving factor analysis , 1991 .
[11] Jostein Toft,et al. Evolutionary rank analysis applied to multidetectional chromatographic structures , 1995 .
[12] A. Savitzky,et al. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .
[13] I. Warner,et al. Rank estimation of excitation-emission matrices using frequency analysis of eigenvectors. , 1986, Analytical chemistry.
[14] Peter D. Wentzell,et al. Parallel Kalman filters for peak purity analysis: extensions to non-ideal detector response , 1995 .
[15] C. Heckler,et al. Self-modeling mixture analysis of categorized pyrolysis mass spectral data with the SIMPLISMA approach , 1992 .
[16] I. Jolliffe. Principal Component Analysis , 2002 .
[17] R. Brereton,et al. Resolution of on‐flow LC/NMR data by multivariate methods — a comparison , 2002 .
[18] Olav M. Kvalheim,et al. Determination of chemical rank of two-way data from mixtures using subspace comparisons , 2000 .
[19] R. Cattell. The Scree Test For The Number Of Factors. , 1966, Multivariate behavioral research.
[20] D. W. Osten,et al. Selection of optimal regression models via cross‐validation , 1988 .
[21] S. Wold. Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models , 1978 .
[22] Edmund R. Malinowski,et al. Determination of the number of factors and the experimental error in a data matrix , 1977 .
[23] Paul Geladi,et al. Principal Component Analysis , 1987, Comprehensive Chemometrics.
[24] Roland F. Hirsch,et al. Reliability of factor analysis in the presence of random noise or outlying data , 1987 .
[25] T. J. Klingen,et al. Correlation of retention volumes of substitutued carboranes with molecular properties in high pressure liquid chromatography using factor analysis , 1974 .
[26] Nicolaas M. Faber. Modification of Malinowski's F-test for Pseudo Rank Estimation Revisited , 1999, Comput. Chem..
[27] R. Brereton,et al. Resolution of on-flow liquid chromatography proton nuclear magnetic resonance using canonical correlation and constrained linear regression , 2002 .
[28] R. Brereton,et al. Evaluation of chemometric methods for determining the number and position of components in high-performance liquid chromatography detected by diode array detector and on-flow 1H nuclear magnetic resonance spectroscopy , 2003 .
[29] Stephen G. Walburn,et al. Collection and analysis of hazardous organic emissions , 1982 .
[30] Milan Meloun,et al. Critical comparison of methods predicting the number of components in spectroscopic data , 2000 .
[31] Olav M. Kvalheim,et al. Eigenstructure tracking analysis for revealing noise pattern and local rank in instrumental profiles: application to transmittance and absorbance IR spectroscopy , 1993 .
[32] J. Mandel. A New Analysis of Variance Model for Non-additive Data , 1971 .
[33] Edmund R. Malinowski,et al. Factor Analysis in Chemistry , 1980 .
[34] D. Massart,et al. Determination of the number of components during mixture analysis using the Durbin–Watson criterion in the Orthogonal Projection Approach and in the SIMPLe-to-use Interactive Self-modelling Mixture Analysis approach , 2002 .
[35] Edmund R. Malinowski,et al. Abstract factor analysis of data with multiple sources of error and a modified Faber–Kowalski f‐test † , 1999 .
[36] Peter D. Wentzell,et al. Real-Time Principal Component Analysis Using Parallel Kalman Filter Networks for Peak Purity Analysis , 1991 .
[37] D. Massart,et al. Orthogonal projection approach applied to peak purity assessment. , 1996, Analytical chemistry.
[38] Characterization of the effect of peak shifts on the performance of the Kalman filter in multicomponent analyses , 1989 .
[39] Alan S. Stern,et al. NMR Data Processing , 1996 .
[40] R. Brereton,et al. Chemometric methods for determination of selective regions in diode array detection high performance liquid chromatography of mixtures: application to chlorophyll a allomers , 1998 .
[41] Laila Stordrange,et al. The morphological score and its application to chemical rank determination , 2000 .
[42] M. Maeder. Evolving factor analysis for the resolution of overlapping chromatographic peaks , 1987 .
[43] N. Ohta,et al. Estimating absorption bands of component dyes by means of principal component analysis , 1973 .
[44] Desire L. Massart,et al. Multivariate peak purity approaches , 1996 .
[45] Sarah C. Rutan,et al. Kalman filtering approaches for solving problems in analytical chemistry , 1987 .
[46] N. Draper,et al. Applied Regression Analysis , 1967 .
[47] Mikael Kubista,et al. An automated procedure to predict the number of components in spectroscopic data , 1999 .