Análisis estadístico de datos multivariados

Gráficas y tablas

Autores:
Díaz Monroy, Luis Guillermo
Morales Rivera, Mario Alfonso
Tipo de recurso:
Book
Fecha de publicación:
2012
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/79916
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/79916
https://repositorio.unal.edu.co/
Palabra clave:
510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas
Análisis multivariante
Estadística matemática
Análisis de varianza
Análisis de conglomerados
Análisis estadístico
Inferencia multivariada
Rights
openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional
id UNACIONAL2_3a8bf063e04996e03058cf01775bb691
oai_identifier_str oai:repositorio.unal.edu.co:unal/79916
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Análisis estadístico de datos multivariados
title Análisis estadístico de datos multivariados
spellingShingle Análisis estadístico de datos multivariados
510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas
Análisis multivariante
Estadística matemática
Análisis de varianza
Análisis de conglomerados
Análisis estadístico
Inferencia multivariada
title_short Análisis estadístico de datos multivariados
title_full Análisis estadístico de datos multivariados
title_fullStr Análisis estadístico de datos multivariados
title_full_unstemmed Análisis estadístico de datos multivariados
title_sort Análisis estadístico de datos multivariados
dc.creator.fl_str_mv Díaz Monroy, Luis Guillermo
Morales Rivera, Mario Alfonso
dc.contributor.author.none.fl_str_mv Díaz Monroy, Luis Guillermo
Morales Rivera, Mario Alfonso
dc.contributor.other.none.fl_str_mv Morales Rivera, Mario Alfonso
Llanos, Willian Javier
dc.subject.ddc.spa.fl_str_mv 510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas
topic 510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas
Análisis multivariante
Estadística matemática
Análisis de varianza
Análisis de conglomerados
Análisis estadístico
Inferencia multivariada
dc.subject.lemb.spa.fl_str_mv Análisis multivariante
Estadística matemática
Análisis de varianza
dc.subject.proposal.spa.fl_str_mv Análisis de conglomerados
Análisis estadístico
Inferencia multivariada
description Gráficas y tablas
publishDate 2012
dc.date.issued.none.fl_str_mv 2012
dc.date.accessioned.none.fl_str_mv 2021-08-11T16:25:06Z
dc.date.available.none.fl_str_mv 2021-08-11T16:25:06Z
dc.type.spa.fl_str_mv Libro
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/book
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2f33
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/LIB
format http://purl.org/coar/resource_type/c_2f33
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/79916
dc.identifier.instname.spa.fl_str_mv Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv https://repositorio.unal.edu.co/
url https://repositorio.unal.edu.co/handle/unal/79916
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.ispartofseries.none.fl_str_mv Colección textos;
dc.relation.citationedition.spa.fl_str_mv Primera edición
dc.relation.references.spa.fl_str_mv Alfenderfer, M. S. & Blashfield, R. (1984), Cluster Analysis, Quantitative Applications in the Social Sciences, Sage Publications, Beverly Hills.
Anderson, T. W. (1984), An Introduction to Multivariate Statistical Analysis, John Wiley and Sons.
Andrews, D. F. (1972), ‘Plots of high-dimensional data’, Biometrics 28, 125– 136.
Andrews, D. F., Gnanadesikan, R. & Warner, J. L. (1973), Methods for Assessing Multivariate Normality, Vol. 3 of Multivariate Analysis, Academic Press, New York.
Anjos, U. et al. (2004), Modelando Depêndencias via Copulas, SINAPE, Caxambu, Minas Gerais.
Arnold, S. F. (1981), The Theory of Linear Models and Multivariate Analysis, John Wiley and Sons.
Bartlett, M. S. (1937), ‘Properties of sufficiency and statistical tests’, Proceedings of the Royal Society of London 160, 268–282.
Bartlett, M. S. (1939), ‘A note on test of significance in multivariate analysis’, Proceedings of the Cambridge Philosophical Society 35, 180–185.
Bartlett, M. S. (1947), ‘Multivariate analysis’, Journal of the Royal Statistical Society (9), 176–197.
Bartlett, M. S. (1954), ‘A note on multiplying factors for various chi-squared approximations’, Journal of the Royal Statistical Society 16, 296–298.
Benzecri, J. P. (1964), Cours de Linguistique Mathématique, Publication multigraphiée, Faculté des Sciences de Rennes.
Biscay, R., Valdes, P. & Pascual, R. (1990), ‘Modified fisher’s linear discriminant function with reduction of dimensionality’, Statistical Computation and simulation 36, 1–8.
Borg, I. & Groenen, P. (1997), Modern Multidimensional Scaling, Springer, New York.
Box, G. E. P. (1949), ‘A general distribution theory for a class of likelihood criteria’, Biometrika 36, 317–346.
Box, G. E. P. & Cox, D. R. (1964), ‘An analysis of transformations’, Journal of the Royal Statistical Society 26, 211–252.
Buck, S. F. A. (1960), ‘A method of estimation of missing values in multivariate data suitable for use with an electronic computer’, Journal of the Royal Statistics Society 22, 302–307.
Butts, C. T. (2009), yacca: Yet Another Canonical Correlation Analysis Package. R package version 1.1.
Chatfield, C. & Collins, A. J. (1986), Introduction to Multivariate Analysis, Chapman & Hall, New York.
Cherkassky, V., Friedman, J. & Wechsler, H. (1993), From Statistics to Neural Networks, theory and Pattern Recognition Applications, Springer, Berlin.
Chernoff, H. (1973), ‘Using faces to represent points in k-dimensional space graphically’, Journal of the American Statistics Association 68, 361–368.
Clifford, H. & Stephenson, W. (1975), Introduction to Numerical Taxonomic, Academic Press, New York.
Cox, T. F. & Cox, M. A. (1994), Multidimensional Scaling, Chapman Hall, London.
Crisci, J. V. & López, M. F. (1983), Introducción a la Teoría y Práctica de la Taxonomía Numérica, Secretaría General de la OEA, Washington, D. C.
D’Agostino, R. B. & Pearson, E. S. (1973), ‘Test for deperture from normality. empirical results for the distributions of b 2 and √ b 1’, Biometrika 60, 60, 613–622.
D´ıaz, L. G. & López, L. A. (1992), ‘Tamaño de muestra en diseño experimental’, Memorias III Simposio de Estadística pp. 132–154.
Diday, E. (1972), ‘Optimisation en classification automatique et reconnnaisance des formes’, Revue Française de Recherche Opérationnelle 3, 61–96.
Dillon, W. R. & Goldstein, M. (1984), Multivariate Analysis, Methods and Applications, John Wiley and Sons, New York.
Efron, B. & Tibshirani, R. (1993), An Introduction to the Bootstrap, Chapman and Hall, London.
Escofier, B. & Pages, J. (1990), Analyses factorielles simples et multiples, Dunod, Paris.
Everitt, B. S. (1980), Cluster Analysis, Heineman Educational Books, London.
Everitt, B. S. & Dunn, G. (1991), Applied Multivariate Data Analysis, Edward Arnold Books, New York.
Frank, M. (1979), ‘On the simultaneous associativity of f(x, y) and x + y − f(x, y)’, Aequationes Math 19(2–3).
Freund, R. J., Litell, R. C. & Spector, P. C. (1986), SAS system for linear models, SAS Institute Inc., Cary, NC.
Genest, C., Ghoudi, K. & Rivest, L. (1995), ‘A semiparametric estimation procedure of dependence parameters in multivariate families of distributions’, Biometrika 82, 543–552.
Genest, C. & Rémillard, B. (2004), ‘Tests of independence and randomness based on the empirical copula process’, Test 2(13), 335–369.
Genest, C. & Rémillard, B. (2008), ‘Validity of the parametric bootstrap for goodness-of-fit testing in semiparametric models’, Annales de l’Institut Henri Poincaré: Probabilités et Statistiques 44, 1096–1127.
Genest, C., Rémillard, B. & Beaudoin, D. (2009), ‘Goodness-of-fit tests for copulas: A review and a power study’, Insurance: Mathematics and Economics 44, 199–213.
Giri, N. C. (1977), Multivariate Statistical Inference, Academic Press, New York. Gnanadesikan, R. (1997), Methods for Statistical Analysis of Multivariate Observations, John Wiley and Sons, New York.
Gnanadesikan, R. & Kattenring, J. R. (1972), ‘Robust stimates, residulas and outlier detection with multiresponse data’, Biometrics pp. 81–124.
Gordon, A. D. (1937), ‘A review of hierarchical classification gordon, a. d.gordon, a. d.’, Journal of the Royal Statistical Society .
Gorsuch, R. L. (1983), Factor Analysis, Lawrence Erlbaum Associates, Publishers, London.
Graybill, F. (2001), Matrices with Applications in Statistics, Duxbury Press.
Gupta, A. & Nagar, D. (2000), Matrix Variate Distributions, Monographs and Surveys in Pure and Applied Mathematics, Chapman & Hall / CRC, New York.
Harville, D. A. (1997), Matrix Algebra from a Statistician’s Perspective, Springer, New York.
Hogg, R. V., Craig, A. T. & Joseph, W. M. (2004), Introduction to Mathematical Statistics, Macmillan Publishing Co. Inc., New York.
Hotelling, H. (1931), ‘The generalization of student’s ratio’, Annals of Mathematical Statistics 2, 360–378.
Hotelling, H. (1947), A generalized T test and measure of multivariate dispersion, Technical report, Berkeley.
Hotelling, H. (1951), ‘The impact of ra fisher on statistics’, Journal of the American Statistical Association pp. 35–46.
Jobson, J. D. (1992), Applied Multivariate Data Analysis, Vol. 1, Springer, New York.
Joe, H. (1993), ‘Parametric family of multivariate distributions with given margins’, Journal of Multivariate Analysis pp. 262–282.
Joe, H. (1997), Multivariate Models and Dependence Concepts, Chapman & Hall CRC, London.
Johnson, D. E. (2000), Métodos multivariados aplicados al análisis de datos, Thomson Editores, México.
Johnson, R. & Wicher, D. W. (1998), Applied Multivariate Statistical Analysis, Prentice Hall, Inc., New Jersey.
Jöreskog, K. G. (1967), ‘Some contributions to maximum likelihood factor analysis’, Psychometrika 32, 443–482.
Kaiser, K. G. (1958), ‘The varimax criteriom for analytic rotation in factor analysis’, Psychometrika 23, 187–200.
Kaiser, K. G. (1967), ‘Some contributions to maximum likelihood factor analysis’, Psychometrika 32, 443–482.
Kim, G., Silvapulle, M., J. & Silvapulle, P. (2007), ‘Comparison of semiparametric and parametric methods for estimating copulas.’, Computational Statistics and Data Analysis 6(51), 2836–2850.
Kojadinovic, I. & Yan, J. (2010), ‘A goodness-of-fit test for multivariate multiparameter copulas based on multiplier central limit theorems’, Statistics and Computing.
Kotz, S. & Fang, H. (2002), ‘The meta-elliptical distributions with given marginals.’, Multivar Anal 1(82), 1–16.
Kotz, S. & Mari, D. (2001), Correlation and Dependence, Imperial College Press, London. Kruskal, J. B. & Wish, M. (1978), Multidimensional Scaling, Sage Publications, Beverly Hills.
Krzanowski, W. J. (1995), Recent Advances in Descriptive Multivariate Analysis, Royal Statistical Society Lecture Note, Oxford University Press, USA.
Krzanowski, W. J. & Marriot, F. H. C. (1994), Multivariate Analysis. Part 1 Distributions, Ordination and Inference, Edward Arnold, London.
Krzanowski, W. J. & Marriot, F. H. C. (1995), Multivariate Analysis. Part 2 Classification, covariance structures and repeated measurements, Edward Arnold, London.
Lawley, D. N. (1938), ‘A generalization of fisher’s z test’, Biometrika 30, 180– 187.
Lawley, D. N. (1967), ‘Some new results in maximum likelihood factor analysis’, Proceedings of the Royal Society of Education 67.
Lebart, L., Morineau, A. & Fénelon, J. P. (1985), Tratamiento Estadístico de Datos, Marcombo-Boixareu Editores, Barcelona.
Lebart, L., Morineau, A. & Piron, M. (1995), Statistique Exploratoire Multidimensionnelle, Dunod, Paris.
Lebart, L., Morineau, A. & Warwick, K. M. (1984), Multivariate Descriptive Statistical Analysis, John Wiley and Sons, New York.
Lee, K. L. (1979), ‘Multivariate test for cluster’, Journal of the American Statistical Association 74, 708–714.
Linares, G. (2001), ‘Escalamiento multidimensional: conceptos y enfoques’, Revista investigación operacional 22(2), 173–183.
Little, R. J. & Rubin, D. B. (1987), Statistical Analysis with Missing Data, John Wiley and Sons, New York.
Maclachlan, G. J. (1992), Discriminant Analysis and Statistical Pattern Recognition, John Wiley and Sons, New York.
Magnus, J. R. & Neudecker, H. (1999), Matrix Differential Calculus with Applications in Statistics and Econometrics, Wiley, New York.
Manly, B. F. J. (2000), Multivariate Statistical Methods: A Primer, Chapman and Hall, New York.
Mantilla, I. (2004), Análisis numérico, Universidad Nacional de Colombia, Bogotá, DC.
Mardia, K. V. (1970), ‘Measures of multivariate skewness and kurtosis with applications’, Biometrika 57, 519–530.
Mardia, K. V., Kent, J. T. & Bibby, J. M. (1979), Multivariate Analysis, Academic Press, New York.
Mason, R. L., Tracy, N. D. & Young, J. C. (1995), ‘Decomposition of t 2 for multivariate control chart interpretation’, Journal of Quality Technology 27(2), 157–158.
Mijares, T. A. (1990), ‘The normal approximation to the bartlett- nanda-pillai trace test in multivariate analysis’, Biometrika 77, 230–233.
Milligan, G. W. & Cooper, M. C. (1985), ‘An examination of procedures for determining the number of cluster’, Psychometrika 50, 159–179.
Mood, A. M., Graybill, F. A. & Boes, D. C. (1982), Introduction to the Theory of Statistics, Mc Graw Hill Book Company, Singapore.
Morrison, D. F. (1990), Multivariate Statistical Methods, Mc Graw Hill Book Company, New York.
Muirhead, R. J. (1982), Aspects of Multivariate Statistical Theory, John Wiley and Sons, New York.
Nagarsenker, B. N. & Pillai, K. C. S. (1974), ‘Distribution of the likelihood ratio for testing Σ = Σ 0, μ = μ 0’, Journal of multivariate analysis 4, 114–122.
Nanda, D. N. (1950), ‘Distribution of the sum of roots of the determinant equation under a certain condition’, Annals of Mathematical Statistics 21, 432–439.
Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., OHara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H. & Wagner, H. (2011), vegan: Community Ecology Package. R package version 1.17-10.
O’Sullivan, J. & Mahon, C. (1966), ‘Glucose tolerance test: variability in pregnant and non–pregnant women’, American Journal of Clinical Nutrition 19, 345–351.
Pan, J.-X. (2002), Growth Curve Models and Statistical Diagnostic, Springer. Pardo, C. E. (1992), Análisis de la aplicación del método de ward de clasificación jerárquica al caso de variables cualitativas, Master’s thesis, Universidad Nacional de Colombia, Santafé de Bogotá, D. C.
Peck, R., Fisher, L. & Van, J. (1989), ‘Approximate confidence intervals for the number of cluster’, Journal of the American Statistical Association 84, 184–191.
Peña, D. (1998), Estadística modelos y métodos. Fundamentos, Alianza Universitaria Textos, Madrid.
Pillai, K. C. S. (1955), ‘Some new test criteria in multivariate analysis’, Annals of Mathematical Statistics 26, 117–121.
Potthoff, R. & Roy, S. (1964), ‘A generalized multivariate analysis model useful especially for growth curve problems’, Biometrika 51, 313–326.
Ramsay, J. & Silverman, B. W. (2005), Funcional Data Analysis, Springer.
Rémillard, B. & Scaillet, O. (2009), ‘Testing for equality between two copulas’, Journal of Multivariate Analysis 100(3), 377–386.
Rencher, A. C. (1995), Methods of Multivariate Analysis, John Wiley and Sons, New York.
Rencher, A. C. (1998), Multivariate Statistical Inference and Applications, John Wiley and Sons, New York.
Rota, G. (1964), ‘On the foundations of combinatorial theory. i. theory of möbius functions’, Zeitschrift f¨ur Wahrscheinlichkeitstheorie und verwandte Gebiete 2, 340–368.
Roussas, G. G. (1973), A First Course in Mathematical Statistics, AddisonWesley Publishing Company, Massachusetts.
Roy, S. N. (1953), ‘On a heuristic method of test construction and its use in multivariate analysis’, Annals of Mathematical Statistics 24.
Roy, S. N. (1957), Some Aspects of multivariate Analysis, John Wiley and Sons, New York.
Ruiz-Velazco, S. (1991), ‘Asympototic efficiency of logistic regression relative to linear discriminant analysis’, Biometrika 78, 235–243.
Saporta, G. (1990), Saporta, Gilbert.Probabilités Analyse des Données et Statistique, Technip, Paris.
Scaillet, O. (2005), ‘A kolmogorov-smirnov type test for positive quadrant dependence.’, Canadian Journal of Statistics, pp. 415–427.
Searle, S. R. (1990), Matrix Algebra Useful for Statistics, John Wiley and Sons, New York.
Seber, G. A. F. (1984), Multivariate observations, John Wiley and Sons, New York.
Seber, G. A. F. (2007), A Matrix Handbook for Statisticians, Wiley Interscience.
Shapiro, S. S. & Wilk, M. B. (1965), ‘An analysis of variance test for normality (complete samples)’, Biometrika 52((3-4)), 591–611.
Sharma, S. (1996), Applied Multivariate TechniquesSharma, Subhash, Jonhn Wiley and Sons, New York.
Sklar, A. (1959), ‘Fonctions de répartition ´a n dimensions et marges’, Publications de l’Institut de Statistique de l’Université de Paris 8, 229–231.
Sokal, R. & Michener, C. D. (1958), A statistical method for evaluating systematic relationship, University of Kansas Scientific Bulletin.
Takane, Y., Young, F. W. & Leeuw, J. (1977), ‘Nonmetric individual differences multidimensional scaling: an alternating least squares method with optimal scaling features’, Psychometrika 42, 7–67.
Team, R. D. C. (2009), R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.
Thompson, P. A. (1995), ‘Correspondence analysis in statistical package programs’, The American Statistician 49, 310–316.
Torres, L. G., Niño, L. F. & Hernández, G. (1993), ‘Redes neuronales’, Memorias, X Coloquio Distrital de Matemáticas y Estadística .
Tukey, J. W. (1957), ‘On the comparative anatomy of transformations’, Annals of Mathematical Statistics 28, 602–632.
Velilla, S. & Barrio, J. A. (1994), ‘A discriminant rule under transformation’, Technometrics 36, 348–353.
Venables, W. N. & Ripley, B. D. (2002), Modern Applied Statistics with S, Springer.
Ward, J. (1963), ‘Approximate confidence intervals for the number of cluster’, Journal of the American Statistical Association 58, 236–224.
Welch, B. L. (1937), ‘The significance of the difference between two means when the population variances are unequal’, Biometrika 29, 350–360.
Welch, B. L. (1947), ‘The generalization of “student” problem when several different population variances are involved’, Biometrika 34, 28–35.
Wilcox, R. R. (1997), Introduction to Robust Stimation and Hipothesis Testing Wilcox, Rand R., Academic Press, New York.
Xu, J. J. (1996), Statistical Modelling and Inference for Multivariate and Longitudinal Discrete Response Data, PhD thesis, Departament of Statistics, University of British Columbia.
Yager, R. R., Ovchinnikov, S., Togn, R. M. & Nguyen, H. T. (1987), Fuzzy Sets and Applications. Selected Papers by L. A. Zadeh, John Wiley and Sons, New York.
Yan, J. (2007), ‘Enjoy the joy of copulas: With a package copula’, Journal of Statistical Software 4(21), 1–21.
Yan, S. S. & Lee, Y. (1987), ‘Identification of a multivariate outlier’, Annual Meeting of the American Statistical Association.
Yeo, I. & Johnson, R. A. (2000), ‘A new family of power transformations to improve normality or symemtry’, Biometrika .
Zadeh, L. A. (1965), ‘Fuzzy sets’, Information and Control pp. 338–353.
dc.rights.spa.fl_str_mv Derechos Reservados al Autor, 2012
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 4.0 Internacional
Derechos Reservados al Autor, 2012
http://creativecommons.org/licenses/by-nc-nd/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.extent.spa.fl_str_mv xxv, 635 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia
dc.publisher.department.spa.fl_str_mv Sede Bogotá
dc.publisher.place.spa.fl_str_mv Bogotá, Colombia
institution Universidad Nacional de Colombia
bitstream.url.fl_str_mv https://repositorio.unal.edu.co/bitstream/unal/79916/2/An%c3%a1lisis%20Estad%c3%adstico%20de%20Datos%20Multivariados%209789587751062.pdf
https://repositorio.unal.edu.co/bitstream/unal/79916/1/license.txt
https://repositorio.unal.edu.co/bitstream/unal/79916/3/4%20An%c3%a1lisis%20estad%c3%adstico%20de%20datos%20%28cub%29.png
https://repositorio.unal.edu.co/bitstream/unal/79916/4/An%c3%a1lisis%20Estad%c3%adstico%20de%20Datos%20Multivariados%209789587751062.pdf.jpg
bitstream.checksum.fl_str_mv 9e5533e0793ef9463b8e4e55afbacbed
cccfe52f796b7c63423298c2d3365fc6
04bf37edcbeaa60251c048a0495f7796
256dc3a013d48f2522149177b6e75119
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
repository.mail.fl_str_mv repositorio_nal@unal.edu.co
_version_ 1814089441325613056
spelling Atribución-NoComercial-SinDerivadas 4.0 InternacionalDerechos Reservados al Autor, 2012http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Díaz Monroy, Luis Guillermo3efc00220cfd299ea4420a319834eeadMorales Rivera, Mario Alfonso87959a6a6e45f3dc016b5230cbe4bd00Morales Rivera, Mario AlfonsoLlanos, Willian Javier2021-08-11T16:25:06Z2021-08-11T16:25:06Z2012https://repositorio.unal.edu.co/handle/unal/79916Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/Gráficas y tablasLa intención al escribir este texto, es ofrecer un material actualizado de análisis y métodos estadísticos multivariados, de fácil acceso para estadísticos y usuarios de la estadística de diferentes disciplinas y áreas del conocimiento. Aunque existe una buena cantidad de esta literatura, son escasos los textos en el idioma español o los que traten varias temáticas de la estadística multivariada a la vez. El orden, el desarrollo didáctico y la presentación de los temas se ha hecho pensando en un lector que posea algunos elementos básicos de matemáticas y de la estadística exploratoria e inferencial. No obstante, se han anexado algunos tópicos de álgebra lineal (Apéndice A) y de estadística univariada (Apéndice B), con los cuales el interesado puede llenar los posibles vacíos que posea en estas áreas o acudir a ellos cuando requiera para avanzar y aprovechar los tópicos presentados. (Texto tomado de la fuente).Incluye apéndices e índice analíticoISBN de la versión impresa 9789587613254Primera ediciónxxv, 635 páginasapplication/pdfspaUniversidad Nacional de ColombiaSede BogotáBogotá, ColombiaColección textos;Primera ediciónAlfenderfer, M. S. & Blashfield, R. (1984), Cluster Analysis, Quantitative Applications in the Social Sciences, Sage Publications, Beverly Hills.Anderson, T. W. (1984), An Introduction to Multivariate Statistical Analysis, John Wiley and Sons.Andrews, D. F. (1972), ‘Plots of high-dimensional data’, Biometrics 28, 125– 136.Andrews, D. F., Gnanadesikan, R. & Warner, J. L. (1973), Methods for Assessing Multivariate Normality, Vol. 3 of Multivariate Analysis, Academic Press, New York.Anjos, U. et al. (2004), Modelando Depêndencias via Copulas, SINAPE, Caxambu, Minas Gerais.Arnold, S. F. (1981), The Theory of Linear Models and Multivariate Analysis, John Wiley and Sons.Bartlett, M. S. (1937), ‘Properties of sufficiency and statistical tests’, Proceedings of the Royal Society of London 160, 268–282.Bartlett, M. S. (1939), ‘A note on test of significance in multivariate analysis’, Proceedings of the Cambridge Philosophical Society 35, 180–185.Bartlett, M. S. (1947), ‘Multivariate analysis’, Journal of the Royal Statistical Society (9), 176–197.Bartlett, M. S. (1954), ‘A note on multiplying factors for various chi-squared approximations’, Journal of the Royal Statistical Society 16, 296–298.Benzecri, J. P. (1964), Cours de Linguistique Mathématique, Publication multigraphiée, Faculté des Sciences de Rennes.Biscay, R., Valdes, P. & Pascual, R. (1990), ‘Modified fisher’s linear discriminant function with reduction of dimensionality’, Statistical Computation and simulation 36, 1–8.Borg, I. & Groenen, P. (1997), Modern Multidimensional Scaling, Springer, New York.Box, G. E. P. (1949), ‘A general distribution theory for a class of likelihood criteria’, Biometrika 36, 317–346.Box, G. E. P. & Cox, D. R. (1964), ‘An analysis of transformations’, Journal of the Royal Statistical Society 26, 211–252.Buck, S. F. A. (1960), ‘A method of estimation of missing values in multivariate data suitable for use with an electronic computer’, Journal of the Royal Statistics Society 22, 302–307.Butts, C. T. (2009), yacca: Yet Another Canonical Correlation Analysis Package. R package version 1.1.Chatfield, C. & Collins, A. J. (1986), Introduction to Multivariate Analysis, Chapman & Hall, New York.Cherkassky, V., Friedman, J. & Wechsler, H. (1993), From Statistics to Neural Networks, theory and Pattern Recognition Applications, Springer, Berlin.Chernoff, H. (1973), ‘Using faces to represent points in k-dimensional space graphically’, Journal of the American Statistics Association 68, 361–368.Clifford, H. & Stephenson, W. (1975), Introduction to Numerical Taxonomic, Academic Press, New York.Cox, T. F. & Cox, M. A. (1994), Multidimensional Scaling, Chapman Hall, London.Crisci, J. V. & López, M. F. (1983), Introducción a la Teoría y Práctica de la Taxonomía Numérica, Secretaría General de la OEA, Washington, D. C.D’Agostino, R. B. & Pearson, E. S. (1973), ‘Test for deperture from normality. empirical results for the distributions of b 2 and √ b 1’, Biometrika 60, 60, 613–622.D´ıaz, L. G. & López, L. A. (1992), ‘Tamaño de muestra en diseño experimental’, Memorias III Simposio de Estadística pp. 132–154.Diday, E. (1972), ‘Optimisation en classification automatique et reconnnaisance des formes’, Revue Française de Recherche Opérationnelle 3, 61–96.Dillon, W. R. & Goldstein, M. (1984), Multivariate Analysis, Methods and Applications, John Wiley and Sons, New York.Efron, B. & Tibshirani, R. (1993), An Introduction to the Bootstrap, Chapman and Hall, London.Escofier, B. & Pages, J. (1990), Analyses factorielles simples et multiples, Dunod, Paris.Everitt, B. S. (1980), Cluster Analysis, Heineman Educational Books, London.Everitt, B. S. & Dunn, G. (1991), Applied Multivariate Data Analysis, Edward Arnold Books, New York.Frank, M. (1979), ‘On the simultaneous associativity of f(x, y) and x + y − f(x, y)’, Aequationes Math 19(2–3).Freund, R. J., Litell, R. C. & Spector, P. C. (1986), SAS system for linear models, SAS Institute Inc., Cary, NC.Genest, C., Ghoudi, K. & Rivest, L. (1995), ‘A semiparametric estimation procedure of dependence parameters in multivariate families of distributions’, Biometrika 82, 543–552.Genest, C. & Rémillard, B. (2004), ‘Tests of independence and randomness based on the empirical copula process’, Test 2(13), 335–369.Genest, C. & Rémillard, B. (2008), ‘Validity of the parametric bootstrap for goodness-of-fit testing in semiparametric models’, Annales de l’Institut Henri Poincaré: Probabilités et Statistiques 44, 1096–1127.Genest, C., Rémillard, B. & Beaudoin, D. (2009), ‘Goodness-of-fit tests for copulas: A review and a power study’, Insurance: Mathematics and Economics 44, 199–213.Giri, N. C. (1977), Multivariate Statistical Inference, Academic Press, New York. Gnanadesikan, R. (1997), Methods for Statistical Analysis of Multivariate Observations, John Wiley and Sons, New York.Gnanadesikan, R. & Kattenring, J. R. (1972), ‘Robust stimates, residulas and outlier detection with multiresponse data’, Biometrics pp. 81–124.Gordon, A. D. (1937), ‘A review of hierarchical classification gordon, a. d.gordon, a. d.’, Journal of the Royal Statistical Society .Gorsuch, R. L. (1983), Factor Analysis, Lawrence Erlbaum Associates, Publishers, London.Graybill, F. (2001), Matrices with Applications in Statistics, Duxbury Press.Gupta, A. & Nagar, D. (2000), Matrix Variate Distributions, Monographs and Surveys in Pure and Applied Mathematics, Chapman & Hall / CRC, New York.Harville, D. A. (1997), Matrix Algebra from a Statistician’s Perspective, Springer, New York.Hogg, R. V., Craig, A. T. & Joseph, W. M. (2004), Introduction to Mathematical Statistics, Macmillan Publishing Co. Inc., New York.Hotelling, H. (1931), ‘The generalization of student’s ratio’, Annals of Mathematical Statistics 2, 360–378.Hotelling, H. (1947), A generalized T test and measure of multivariate dispersion, Technical report, Berkeley.Hotelling, H. (1951), ‘The impact of ra fisher on statistics’, Journal of the American Statistical Association pp. 35–46.Jobson, J. D. (1992), Applied Multivariate Data Analysis, Vol. 1, Springer, New York.Joe, H. (1993), ‘Parametric family of multivariate distributions with given margins’, Journal of Multivariate Analysis pp. 262–282.Joe, H. (1997), Multivariate Models and Dependence Concepts, Chapman & Hall CRC, London.Johnson, D. E. (2000), Métodos multivariados aplicados al análisis de datos, Thomson Editores, México.Johnson, R. & Wicher, D. W. (1998), Applied Multivariate Statistical Analysis, Prentice Hall, Inc., New Jersey.Jöreskog, K. G. (1967), ‘Some contributions to maximum likelihood factor analysis’, Psychometrika 32, 443–482.Kaiser, K. G. (1958), ‘The varimax criteriom for analytic rotation in factor analysis’, Psychometrika 23, 187–200.Kaiser, K. G. (1967), ‘Some contributions to maximum likelihood factor analysis’, Psychometrika 32, 443–482.Kim, G., Silvapulle, M., J. & Silvapulle, P. (2007), ‘Comparison of semiparametric and parametric methods for estimating copulas.’, Computational Statistics and Data Analysis 6(51), 2836–2850.Kojadinovic, I. & Yan, J. (2010), ‘A goodness-of-fit test for multivariate multiparameter copulas based on multiplier central limit theorems’, Statistics and Computing.Kotz, S. & Fang, H. (2002), ‘The meta-elliptical distributions with given marginals.’, Multivar Anal 1(82), 1–16.Kotz, S. & Mari, D. (2001), Correlation and Dependence, Imperial College Press, London. Kruskal, J. B. & Wish, M. (1978), Multidimensional Scaling, Sage Publications, Beverly Hills.Krzanowski, W. J. (1995), Recent Advances in Descriptive Multivariate Analysis, Royal Statistical Society Lecture Note, Oxford University Press, USA.Krzanowski, W. J. & Marriot, F. H. C. (1994), Multivariate Analysis. Part 1 Distributions, Ordination and Inference, Edward Arnold, London.Krzanowski, W. J. & Marriot, F. H. C. (1995), Multivariate Analysis. Part 2 Classification, covariance structures and repeated measurements, Edward Arnold, London.Lawley, D. N. (1938), ‘A generalization of fisher’s z test’, Biometrika 30, 180– 187.Lawley, D. N. (1967), ‘Some new results in maximum likelihood factor analysis’, Proceedings of the Royal Society of Education 67.Lebart, L., Morineau, A. & Fénelon, J. P. (1985), Tratamiento Estadístico de Datos, Marcombo-Boixareu Editores, Barcelona.Lebart, L., Morineau, A. & Piron, M. (1995), Statistique Exploratoire Multidimensionnelle, Dunod, Paris.Lebart, L., Morineau, A. & Warwick, K. M. (1984), Multivariate Descriptive Statistical Analysis, John Wiley and Sons, New York.Lee, K. L. (1979), ‘Multivariate test for cluster’, Journal of the American Statistical Association 74, 708–714.Linares, G. (2001), ‘Escalamiento multidimensional: conceptos y enfoques’, Revista investigación operacional 22(2), 173–183.Little, R. J. & Rubin, D. B. (1987), Statistical Analysis with Missing Data, John Wiley and Sons, New York.Maclachlan, G. J. (1992), Discriminant Analysis and Statistical Pattern Recognition, John Wiley and Sons, New York.Magnus, J. R. & Neudecker, H. (1999), Matrix Differential Calculus with Applications in Statistics and Econometrics, Wiley, New York.Manly, B. F. J. (2000), Multivariate Statistical Methods: A Primer, Chapman and Hall, New York.Mantilla, I. (2004), Análisis numérico, Universidad Nacional de Colombia, Bogotá, DC.Mardia, K. V. (1970), ‘Measures of multivariate skewness and kurtosis with applications’, Biometrika 57, 519–530.Mardia, K. V., Kent, J. T. & Bibby, J. M. (1979), Multivariate Analysis, Academic Press, New York.Mason, R. L., Tracy, N. D. & Young, J. C. (1995), ‘Decomposition of t 2 for multivariate control chart interpretation’, Journal of Quality Technology 27(2), 157–158.Mijares, T. A. (1990), ‘The normal approximation to the bartlett- nanda-pillai trace test in multivariate analysis’, Biometrika 77, 230–233.Milligan, G. W. & Cooper, M. C. (1985), ‘An examination of procedures for determining the number of cluster’, Psychometrika 50, 159–179.Mood, A. M., Graybill, F. A. & Boes, D. C. (1982), Introduction to the Theory of Statistics, Mc Graw Hill Book Company, Singapore.Morrison, D. F. (1990), Multivariate Statistical Methods, Mc Graw Hill Book Company, New York.Muirhead, R. J. (1982), Aspects of Multivariate Statistical Theory, John Wiley and Sons, New York.Nagarsenker, B. N. & Pillai, K. C. S. (1974), ‘Distribution of the likelihood ratio for testing Σ = Σ 0, μ = μ 0’, Journal of multivariate analysis 4, 114–122.Nanda, D. N. (1950), ‘Distribution of the sum of roots of the determinant equation under a certain condition’, Annals of Mathematical Statistics 21, 432–439.Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., OHara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H. & Wagner, H. (2011), vegan: Community Ecology Package. R package version 1.17-10.O’Sullivan, J. & Mahon, C. (1966), ‘Glucose tolerance test: variability in pregnant and non–pregnant women’, American Journal of Clinical Nutrition 19, 345–351.Pan, J.-X. (2002), Growth Curve Models and Statistical Diagnostic, Springer. Pardo, C. E. (1992), Análisis de la aplicación del método de ward de clasificación jerárquica al caso de variables cualitativas, Master’s thesis, Universidad Nacional de Colombia, Santafé de Bogotá, D. C.Peck, R., Fisher, L. & Van, J. (1989), ‘Approximate confidence intervals for the number of cluster’, Journal of the American Statistical Association 84, 184–191.Peña, D. (1998), Estadística modelos y métodos. Fundamentos, Alianza Universitaria Textos, Madrid.Pillai, K. C. S. (1955), ‘Some new test criteria in multivariate analysis’, Annals of Mathematical Statistics 26, 117–121.Potthoff, R. & Roy, S. (1964), ‘A generalized multivariate analysis model useful especially for growth curve problems’, Biometrika 51, 313–326.Ramsay, J. & Silverman, B. W. (2005), Funcional Data Analysis, Springer.Rémillard, B. & Scaillet, O. (2009), ‘Testing for equality between two copulas’, Journal of Multivariate Analysis 100(3), 377–386.Rencher, A. C. (1995), Methods of Multivariate Analysis, John Wiley and Sons, New York.Rencher, A. C. (1998), Multivariate Statistical Inference and Applications, John Wiley and Sons, New York.Rota, G. (1964), ‘On the foundations of combinatorial theory. i. theory of möbius functions’, Zeitschrift f¨ur Wahrscheinlichkeitstheorie und verwandte Gebiete 2, 340–368.Roussas, G. G. (1973), A First Course in Mathematical Statistics, AddisonWesley Publishing Company, Massachusetts.Roy, S. N. (1953), ‘On a heuristic method of test construction and its use in multivariate analysis’, Annals of Mathematical Statistics 24.Roy, S. N. (1957), Some Aspects of multivariate Analysis, John Wiley and Sons, New York.Ruiz-Velazco, S. (1991), ‘Asympototic efficiency of logistic regression relative to linear discriminant analysis’, Biometrika 78, 235–243.Saporta, G. (1990), Saporta, Gilbert.Probabilités Analyse des Données et Statistique, Technip, Paris.Scaillet, O. (2005), ‘A kolmogorov-smirnov type test for positive quadrant dependence.’, Canadian Journal of Statistics, pp. 415–427.Searle, S. R. (1990), Matrix Algebra Useful for Statistics, John Wiley and Sons, New York.Seber, G. A. F. (1984), Multivariate observations, John Wiley and Sons, New York.Seber, G. A. F. (2007), A Matrix Handbook for Statisticians, Wiley Interscience.Shapiro, S. S. & Wilk, M. B. (1965), ‘An analysis of variance test for normality (complete samples)’, Biometrika 52((3-4)), 591–611.Sharma, S. (1996), Applied Multivariate TechniquesSharma, Subhash, Jonhn Wiley and Sons, New York.Sklar, A. (1959), ‘Fonctions de répartition ´a n dimensions et marges’, Publications de l’Institut de Statistique de l’Université de Paris 8, 229–231.Sokal, R. & Michener, C. D. (1958), A statistical method for evaluating systematic relationship, University of Kansas Scientific Bulletin.Takane, Y., Young, F. W. & Leeuw, J. (1977), ‘Nonmetric individual differences multidimensional scaling: an alternating least squares method with optimal scaling features’, Psychometrika 42, 7–67.Team, R. D. C. (2009), R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.Thompson, P. A. (1995), ‘Correspondence analysis in statistical package programs’, The American Statistician 49, 310–316.Torres, L. G., Niño, L. F. & Hernández, G. (1993), ‘Redes neuronales’, Memorias, X Coloquio Distrital de Matemáticas y Estadística .Tukey, J. W. (1957), ‘On the comparative anatomy of transformations’, Annals of Mathematical Statistics 28, 602–632.Velilla, S. & Barrio, J. A. (1994), ‘A discriminant rule under transformation’, Technometrics 36, 348–353.Venables, W. N. & Ripley, B. D. (2002), Modern Applied Statistics with S, Springer.Ward, J. (1963), ‘Approximate confidence intervals for the number of cluster’, Journal of the American Statistical Association 58, 236–224.Welch, B. L. (1937), ‘The significance of the difference between two means when the population variances are unequal’, Biometrika 29, 350–360.Welch, B. L. (1947), ‘The generalization of “student” problem when several different population variances are involved’, Biometrika 34, 28–35.Wilcox, R. R. (1997), Introduction to Robust Stimation and Hipothesis Testing Wilcox, Rand R., Academic Press, New York.Xu, J. J. (1996), Statistical Modelling and Inference for Multivariate and Longitudinal Discrete Response Data, PhD thesis, Departament of Statistics, University of British Columbia.Yager, R. R., Ovchinnikov, S., Togn, R. M. & Nguyen, H. T. (1987), Fuzzy Sets and Applications. Selected Papers by L. A. Zadeh, John Wiley and Sons, New York.Yan, J. (2007), ‘Enjoy the joy of copulas: With a package copula’, Journal of Statistical Software 4(21), 1–21.Yan, S. S. & Lee, Y. (1987), ‘Identification of a multivariate outlier’, Annual Meeting of the American Statistical Association.Yeo, I. & Johnson, R. A. (2000), ‘A new family of power transformations to improve normality or symemtry’, Biometrika .Zadeh, L. A. (1965), ‘Fuzzy sets’, Information and Control pp. 338–353.510 - Matemáticas::519 - Probabilidades y matemáticas aplicadasAnálisis multivarianteEstadística matemáticaAnálisis de varianzaAnálisis de conglomeradosAnálisis estadísticoInferencia multivariadaAnálisis estadístico de datos multivariadosLibroinfo:eu-repo/semantics/bookinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_2f33Texthttp://purl.org/redcol/resource_type/LIBGeneralORIGINALAnálisis Estadístico de Datos Multivariados 9789587751062.pdfAnálisis Estadístico de Datos Multivariados 9789587751062.pdfLibro del Departamento de Estadísticaapplication/pdf4909064https://repositorio.unal.edu.co/bitstream/unal/79916/2/An%c3%a1lisis%20Estad%c3%adstico%20de%20Datos%20Multivariados%209789587751062.pdf9e5533e0793ef9463b8e4e55afbacbedMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83964https://repositorio.unal.edu.co/bitstream/unal/79916/1/license.txtcccfe52f796b7c63423298c2d3365fc6MD51THUMBNAIL4 Análisis estadístico de datos (cub).png4 Análisis estadístico de datos (cub).pngimage/png17942https://repositorio.unal.edu.co/bitstream/unal/79916/3/4%20An%c3%a1lisis%20estad%c3%adstico%20de%20datos%20%28cub%29.png04bf37edcbeaa60251c048a0495f7796MD53Análisis Estadístico de Datos Multivariados 9789587751062.pdf.jpgAnálisis Estadístico de Datos Multivariados 9789587751062.pdf.jpgGenerated Thumbnailimage/jpeg6205https://repositorio.unal.edu.co/bitstream/unal/79916/4/An%c3%a1lisis%20Estad%c3%adstico%20de%20Datos%20Multivariados%209789587751062.pdf.jpg256dc3a013d48f2522149177b6e75119MD54unal/79916oai:repositorio.unal.edu.co:unal/799162024-07-27 00:15:42.739Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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