MVar.pt-package: Analise multivariada (brazilian portuguese).
In MVar.pt: Analise multivariada (brazilian portuguese)
MVar.pt-package R Documentation
Analise multivariada (brazilian portuguese).
Description
Analise multivariada, tendo funcoes que executam analise de correspondencia simples (CA) e multipla (MCA), analise de componentes principais (PCA), analise de correlacao canonica (CCA), analise fatorial (FA), escalonamento multidimensional (MDS), analise discriminante linear (LDA) e quadratica (QDA), analise de cluster hierarquico e nao hierarquico, regressao linear simples e multipla, analise de multiplos fatores (MFA) para dados quantitativos, qualitativos, de frequencia (MFACT) e dados mistos, biplot, scatter plot, projection pursuit (PP), grant tour e outras funcoes uteis para a analise multivariada.
Details
Package: MVar.pt
Type: Package
Version: 2.2.2
Date: 2024-06-21
License: GPL(>= 2)
LazyLoad: yes
Author(s)
Paulo Cesar Ossani e Marcelo Angelo Cirillo.
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>
References
Abdessemed, L.; Escofier, B.; Analyse factorielle multiple de tableaux de frequencies: comparaison avec l'analyse canonique des correspondences. Journal de la Societe de Statistique de Paris, Paris, v. 137, n. 2, p. 3-18, 1996.
Abdi, H. Singular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD). In: SALKIND, N. J. (Ed.). Encyclopedia of measurement and statistics. Thousand Oaks: Sage, 2007. p. 907-912.
Abdi, H.; Valentin, D. Multiple factor analysis (MFA). In: SALKIND, N. J. (Ed.). Encyclopedia of measurement and statistics. Thousand Oaks: Sage, 2007. p. 657-663.
Abdi, H.; Williams, L. Principal component analysis. WIREs Computational Statatistics, New York, v. 2, n. 4, p. 433-459, July/Aug. 2010.
Abdi, H.; Williams, L.; Valentin, D. Multiple factor analysis: principal component analysis for multitable and multiblock data sets. WIREs Computational Statatistics, New York, v. 5, n. 2, p. 149-179, Feb. 2013.
Asimov, D. The Grand Tour: A Tool for Viewing Multidimensional Data. SIAM Journal of Scientific and Statistical Computing, 6(1), 128-143, 1985.
Asimov, D.; Buja, A. The grand tour via geodesic interpolation of 2-frames. in Visual Data Exploration and Analysis. Symposium on Electronic Imaging Science and Technology, IS&T/SPIE. 1994.
Becue-Bertaut, M.; Pages, J. A principal axes method for comparing contingency tables: MFACT. Computational Statistics & Data Analysis, New York, v. 45, n. 3, p. 481-503, Feb. 2004
Becue-Bertaut, M.; Pages, J. Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data. Computational Statistics & Data Analysis, New York, v. 52, n. 6, p. 3255-3268, Feb. 2008.
Benzecri, J. Analyse de l'inertie intraclasse par l'analyse d'un tableau de contingence: intra-classinertia analysis through the analysis of a contingency table. Les Cahiers de l'Analyse des Donnees, Paris, v. 8, n. 3, p. 351-358, 1983.
Buja, A.; Asimov, D. Grand tour methods: An outline. Computer Science and Statistics, 17:63-67. 1986.
Buja, A.; Cook, D.; Asimov, D.; Hurley, C. Computational Methods for High-Dimensional Rotations in Data Visualization, in C. R. Rao, E. J. Wegman & J. L. Solka, eds, "Handbook of Statistics: Data Mining and Visualization", Elsevier/North Holland, http://www.elsevier.com, pp. 391-413. 2005.
Charnet, R., at al. Analise de modelos de regressao lienar, 2a ed. Campinas: Editora da Unicamp, 2008. 357 p.
Cook, D.; Lee, E. K.; Buja, A.; WickmamM, H. Grand tours, projection pursuit guided tours and manual controls. In Chen, Chunhouh, Hardle, Wolfgang, Unwin, e Antony (Eds.), Handbook of Data Visualization, Springer Handbooks of Computational Statistics, chapter III.2, p. 295-314. Springer, 2008.
Cook, D.; Buja, A.; Cabrera, J. Projection pursuit indexes based on orthonormal function expansions. Journal of Computational and Graphical Statistics, 2(3):225-250, 1993.
Cook, D.; Buja, A.; Cabrera, J.; Hurley, C. Grand tour and projection pursuit, Journal of Computational and Graphical Statistics, 4(3), 155-172, 1995.
Cook, D.; Swayne, D. F. Interactive and Dynamic Graphics for Data Analysis: With R and GGobi. Springer. 2007.
Escofier, B. Analyse factorielle en reference a un modele: application a l'analyse d'un tableau d'echanges. Revue de Statistique Appliquee, Paris, v. 32, n. 4, p. 25-36, 1984.
Escofier, B.; Drouet, D. Analyse des differences entre plusieurs tableaux de frequence. Les Cahiers de l'Analyse des Donnees, Paris, v. 8, n. 4, p. 491-499, 1983.
Escofier, B.; Pages, J. Analyse factorielles simples et multiples. Paris: Dunod, 1990. 267 p.
Escofier, B.; Pages, J. Analyses factorielles simples et multiples: objectifs, methodes et interpretation. 4th ed. Paris: Dunod, 2008. 318 p.
Escofier, B.; Pages, J. Comparaison de groupes de variables definies sur le meme ensemble d'individus: un exemple d'applications. Le Chesnay: Institut National de Recherche en Informatique et en Automatique, 1982. 121 p.
Escofier, B.; Pages, J. Multiple factor analysis (AFUMULT package). Computational Statistics & Data Analysis, New York, v. 18, n. 1, p. 121-140, Aug. 1994
Espezua, S.; Villanueva, E.; Maciel, C. D.; Carvalho, A. A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets. Neurocomputing, 149, 767-776, 2015.
Ferreira, D. F. Estatistica multivariada. 2. ed. rev. e ampl. Lavras: UFLA, 2011. 675 p.
Friedman, J. H., Tukey, J. W. A projection pursuit algorithm for exploratory data analysis. IEEE Transaction on Computers, 23(9):881-890, 1974.
Greenacre, M.; Blasius, J. Multiple correspondence analysis and related methods. New York: Taylor and Francis, 2006. 607 p.
Hastie, T.; Buja, A.; Tibshirani, R. Penalized discriminant analysis. The Annals of Statistics. 23(1), 73-102 . 1995.
Hotelling, H. Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology, Arlington, v. 24, p. 417-441, Sept. 1933.
Huber, P. J. Projection pursuit. Annals of Statistics, 13(2):435-475, 1985.
Hurley, C.; Buja, A. Analyzing high-dimensional data with motion graphics, SIAM Journal of Scientific and Statistical Computing, 11 (6), 1193-1211. 1990.
Johnson, R. A.; Wichern, D. W. Applied multivariate statistical analysis. 6th ed. New Jersey: Prentice Hall, 2007. 794 p.
Jones, M. C.; Sibson, R. What is projection pursuit, (with discussion), Journal of the Royal Statistical Society, Series A 150, 1-36, 1987.
Lee, E.; Cook, D.; Klinke, S.; Lumley, T. Projection pursuit for exploratory supervised classification. Journal of Computational and Graphical Statistics, 14(4):831-846, 2005.
Lee, E. K., Cook, D. A projection pursuit index for large p small n data. Statistics and Computing, 20(3):381-392, 2010.
Martinez, W. L.; Martinez, A. R. Computational Statistics Handbook with MATLAB, 2th. ed. New York: Chapman & Hall/CRC, 2007. 794 p.
Martinez, W. L.; Martinez, A. R.; Solka, J. Exploratory Data Analysis with MATLAB, 2th. ed. New York: Chapman & Hall/CRC, 2010. 499 p.
Mingoti, S. A. Analise de dados atraves de metodos de estatistica multivariada: uma abordagem aplicada. Belo Horizonte: UFMG, 2005. 297 p.
Ossani, P. C.; Cirillo, M. A.; Borem, F. M.; Ribeiro, D. E.; Cortez, R. M. Quality of specialty coffees: a sensory evaluation by consumers using the MFACT technique. Revista Ciencia Agronomica (UFC. Online), v. 48, p. 92-100, 2017.
Ossani, P. C. Qualidade de cafes especiais e nao especiais por meio da analise de multiplos fatores para tabelas de contingencias. 2015. 107 p. Dissertacao (Mestrado em Estatistica e Experimentacao Agropecuaria) - Universidade Federal de Lavras, Lavras, 2015.
Pages, J. Analyse factorielle multiple appliquee aux variables qualitatives et aux donnees mixtes. Revue de Statistique Appliquee, Paris, v. 50, n. 4, p. 5-37, 2002.
Pages, J. Multiple factor analysis: main features and application to sensory data. Revista Colombiana de Estadistica, Bogota, v. 27, n. 1, p. 1-26, 2004.
Pena, D.; Prieto, F. Cluster identification using projections. Journal of the American Statistical Association, 96(456):1433-1445, 2001.
Posse, C. Projection pursuit exploratory data analysis, Computational Statistics and Data Analysis, 29:669-687, 1995a.
Posse, C. Tools for two-dimensional exploratory projection pursuit, Journal of Computational and Graphical Statistics, 4:83-100, 1995b
Rencher, A.C.; Methods of Multivariate Analysis. 2th. ed. New York: J.Wiley, 2002. 708 p.
Young, F. W.; Rheingans P. Visualizing structure in high-dimensional multivariate data, IBM Journal of Research and Development, 35:97-107, 1991.
Young, F. W.; Faldowski R. A.; McFarlane M. M. Multivariate statistical visualization, in Handbook of Statistics, Vol 9, C. R. Rao (ed.), The Netherlands: Elsevier Science Publishers, 959-998, 1993.
MVar.pt documentation built on June 22, 2024, 9:34 a.m.
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Analise multivariada (brazilian portuguese).
Description
Analise multivariada, tendo funcoes que executam analise de correspondencia simples (CA) e multipla (MCA), analise de componentes principais (PCA), analise de correlacao canonica (CCA), analise fatorial (FA), escalonamento multidimensional (MDS), analise discriminante linear (LDA) e quadratica (QDA), analise de cluster hierarquico e nao hierarquico, regressao linear simples e multipla, analise de multiplos fatores (MFA) para dados quantitativos, qualitativos, de frequencia (MFACT) e dados mistos, biplot, scatter plot, projection pursuit (PP), grant tour e outras funcoes uteis para a analise multivariada.
Details
| Package: | MVar.pt |
| Type: | Package |
| Version: | 2.2.2 |
| Date: | 2024-06-21 |
| License: | GPL(>= 2) |
| LazyLoad: | yes |
Author(s)
Paulo Cesar Ossani e Marcelo Angelo Cirillo.
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>
References
Abdessemed, L.; Escofier, B.; Analyse factorielle multiple de tableaux de frequencies: comparaison avec l'analyse canonique des correspondences. Journal de la Societe de Statistique de Paris, Paris, v. 137, n. 2, p. 3-18, 1996.
Abdi, H. Singular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD). In: SALKIND, N. J. (Ed.). Encyclopedia of measurement and statistics. Thousand Oaks: Sage, 2007. p. 907-912.
Abdi, H.; Valentin, D. Multiple factor analysis (MFA). In: SALKIND, N. J. (Ed.). Encyclopedia of measurement and statistics. Thousand Oaks: Sage, 2007. p. 657-663.
Abdi, H.; Williams, L. Principal component analysis. WIREs Computational Statatistics, New York, v. 2, n. 4, p. 433-459, July/Aug. 2010.
Abdi, H.; Williams, L.; Valentin, D. Multiple factor analysis: principal component analysis for multitable and multiblock data sets. WIREs Computational Statatistics, New York, v. 5, n. 2, p. 149-179, Feb. 2013.
Asimov, D. The Grand Tour: A Tool for Viewing Multidimensional Data. SIAM Journal of Scientific and Statistical Computing, 6(1), 128-143, 1985.
Asimov, D.; Buja, A. The grand tour via geodesic interpolation of 2-frames. in Visual Data Exploration and Analysis. Symposium on Electronic Imaging Science and Technology, IS&T/SPIE. 1994.
Becue-Bertaut, M.; Pages, J. A principal axes method for comparing contingency tables: MFACT. Computational Statistics & Data Analysis, New York, v. 45, n. 3, p. 481-503, Feb. 2004
Becue-Bertaut, M.; Pages, J. Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data. Computational Statistics & Data Analysis, New York, v. 52, n. 6, p. 3255-3268, Feb. 2008.
Benzecri, J. Analyse de l'inertie intraclasse par l'analyse d'un tableau de contingence: intra-classinertia analysis through the analysis of a contingency table. Les Cahiers de l'Analyse des Donnees, Paris, v. 8, n. 3, p. 351-358, 1983.
Buja, A.; Asimov, D. Grand tour methods: An outline. Computer Science and Statistics, 17:63-67. 1986.
Buja, A.; Cook, D.; Asimov, D.; Hurley, C. Computational Methods for High-Dimensional Rotations in Data Visualization, in C. R. Rao, E. J. Wegman & J. L. Solka, eds, "Handbook of Statistics: Data Mining and Visualization", Elsevier/North Holland, http://www.elsevier.com, pp. 391-413. 2005.
Charnet, R., at al. Analise de modelos de regressao lienar, 2a ed. Campinas: Editora da Unicamp, 2008. 357 p.
Cook, D.; Lee, E. K.; Buja, A.; WickmamM, H. Grand tours, projection pursuit guided tours and manual controls. In Chen, Chunhouh, Hardle, Wolfgang, Unwin, e Antony (Eds.), Handbook of Data Visualization, Springer Handbooks of Computational Statistics, chapter III.2, p. 295-314. Springer, 2008.
Cook, D.; Buja, A.; Cabrera, J. Projection pursuit indexes based on orthonormal function expansions. Journal of Computational and Graphical Statistics, 2(3):225-250, 1993.
Cook, D.; Buja, A.; Cabrera, J.; Hurley, C. Grand tour and projection pursuit, Journal of Computational and Graphical Statistics, 4(3), 155-172, 1995.
Cook, D.; Swayne, D. F. Interactive and Dynamic Graphics for Data Analysis: With R and GGobi. Springer. 2007.
Escofier, B. Analyse factorielle en reference a un modele: application a l'analyse d'un tableau d'echanges. Revue de Statistique Appliquee, Paris, v. 32, n. 4, p. 25-36, 1984.
Escofier, B.; Drouet, D. Analyse des differences entre plusieurs tableaux de frequence. Les Cahiers de l'Analyse des Donnees, Paris, v. 8, n. 4, p. 491-499, 1983.
Escofier, B.; Pages, J. Analyse factorielles simples et multiples. Paris: Dunod, 1990. 267 p.
Escofier, B.; Pages, J. Analyses factorielles simples et multiples: objectifs, methodes et interpretation. 4th ed. Paris: Dunod, 2008. 318 p.
Escofier, B.; Pages, J. Comparaison de groupes de variables definies sur le meme ensemble d'individus: un exemple d'applications. Le Chesnay: Institut National de Recherche en Informatique et en Automatique, 1982. 121 p.
Escofier, B.; Pages, J. Multiple factor analysis (AFUMULT package). Computational Statistics & Data Analysis, New York, v. 18, n. 1, p. 121-140, Aug. 1994
Espezua, S.; Villanueva, E.; Maciel, C. D.; Carvalho, A. A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets. Neurocomputing, 149, 767-776, 2015.
Ferreira, D. F. Estatistica multivariada. 2. ed. rev. e ampl. Lavras: UFLA, 2011. 675 p.
Friedman, J. H., Tukey, J. W. A projection pursuit algorithm for exploratory data analysis. IEEE Transaction on Computers, 23(9):881-890, 1974.
Greenacre, M.; Blasius, J. Multiple correspondence analysis and related methods. New York: Taylor and Francis, 2006. 607 p.
Hastie, T.; Buja, A.; Tibshirani, R. Penalized discriminant analysis. The Annals of Statistics. 23(1), 73-102 . 1995.
Hotelling, H. Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology, Arlington, v. 24, p. 417-441, Sept. 1933.
Huber, P. J. Projection pursuit. Annals of Statistics, 13(2):435-475, 1985.
Hurley, C.; Buja, A. Analyzing high-dimensional data with motion graphics, SIAM Journal of Scientific and Statistical Computing, 11 (6), 1193-1211. 1990.
Johnson, R. A.; Wichern, D. W. Applied multivariate statistical analysis. 6th ed. New Jersey: Prentice Hall, 2007. 794 p.
Jones, M. C.; Sibson, R. What is projection pursuit, (with discussion), Journal of the Royal Statistical Society, Series A 150, 1-36, 1987.
Lee, E.; Cook, D.; Klinke, S.; Lumley, T. Projection pursuit for exploratory supervised classification. Journal of Computational and Graphical Statistics, 14(4):831-846, 2005.
Lee, E. K., Cook, D. A projection pursuit index for large p small n data. Statistics and Computing, 20(3):381-392, 2010.
Martinez, W. L.; Martinez, A. R. Computational Statistics Handbook with MATLAB, 2th. ed. New York: Chapman & Hall/CRC, 2007. 794 p.
Martinez, W. L.; Martinez, A. R.; Solka, J. Exploratory Data Analysis with MATLAB, 2th. ed. New York: Chapman & Hall/CRC, 2010. 499 p.
Mingoti, S. A. Analise de dados atraves de metodos de estatistica multivariada: uma abordagem aplicada. Belo Horizonte: UFMG, 2005. 297 p.
Ossani, P. C.; Cirillo, M. A.; Borem, F. M.; Ribeiro, D. E.; Cortez, R. M. Quality of specialty coffees: a sensory evaluation by consumers using the MFACT technique. Revista Ciencia Agronomica (UFC. Online), v. 48, p. 92-100, 2017.
Ossani, P. C. Qualidade de cafes especiais e nao especiais por meio da analise de multiplos fatores para tabelas de contingencias. 2015. 107 p. Dissertacao (Mestrado em Estatistica e Experimentacao Agropecuaria) - Universidade Federal de Lavras, Lavras, 2015.
Pages, J. Analyse factorielle multiple appliquee aux variables qualitatives et aux donnees mixtes. Revue de Statistique Appliquee, Paris, v. 50, n. 4, p. 5-37, 2002.
Pages, J. Multiple factor analysis: main features and application to sensory data. Revista Colombiana de Estadistica, Bogota, v. 27, n. 1, p. 1-26, 2004.
Pena, D.; Prieto, F. Cluster identification using projections. Journal of the American Statistical Association, 96(456):1433-1445, 2001.
Posse, C. Projection pursuit exploratory data analysis, Computational Statistics and Data Analysis, 29:669-687, 1995a.
Posse, C. Tools for two-dimensional exploratory projection pursuit, Journal of Computational and Graphical Statistics, 4:83-100, 1995b
Rencher, A.C.; Methods of Multivariate Analysis. 2th. ed. New York: J.Wiley, 2002. 708 p.
Young, F. W.; Rheingans P. Visualizing structure in high-dimensional multivariate data, IBM Journal of Research and Development, 35:97-107, 1991.
Young, F. W.; Faldowski R. A.; McFarlane M. M. Multivariate statistical visualization, in Handbook of Statistics, Vol 9, C. R. Rao (ed.), The Netherlands: Elsevier Science Publishers, 959-998, 1993.
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