{"data":{"id":"10.6084/m9.figshare.960499.v1","type":"dois","attributes":{"doi":"10.6084/m9.figshare.960499.v1","prefix":"10.6084","suffix":"m9.figshare.960499.v1","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Maadooliat, Mehdi","nameType":"Personal","givenName":"Mehdi","familyName":"Maadooliat","affiliation":[],"nameIdentifiers":[]},{"name":"Jianhua Z. Huang","affiliation":[],"nameIdentifiers":[]},{"name":"Jianhua Hu","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Integrating Data Transformation in Principal Components Analysis"}],"publisher":"Taylor \u0026 Francis","container":{},"publicationYear":2015,"subjects":[{"subject":"Inorganic Chemistry"},{"subject":"FOS: Chemical sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Chemical sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Mathematics"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Mathematics","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Information and Computing Sciences"},{"subject":"Biotechnology"},{"subject":"Pharmacology"},{"subject":"Genetics"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Biological sciences","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2015-01-02","dateType":"Created"},{"date":"2016-01-18","dateType":"Updated"},{"date":"2015","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1080/10618600.2014.891461","relatedIdentifierType":"DOI"},{"relationType":"IsPreviousVersionOf","relatedIdentifier":"10.6084/m9.figshare.960499","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["0 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Principal component analysis (PCA) is a popular dimension reduction method to reduce the complexity and obtain the informative aspects of high-dimensional datasets. When the data distribution is skewed, data transformation is commonly used prior to applying PCA. Such transformation is usually obtained from previous studies, prior knowledge, or trial-and-error. In this work, we develop a model-based method that integrates data transformation in PCA and finds an appropriate data transformation using the maximum profile likelihood. Extensions of the method to handle functional data and missing values are also developed. Several numerical algorithms are provided for efficient computation. The proposed method is illustrated using simulated and real-world data examples.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://tandf.figshare.com/articles/dataset/Integrating_Data_Transformation_in_Principal_Components_Analysis/960499/1","contentUrl":null,"metadataVersion":3,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"viewsOverTime":[],"downloadCount":0,"downloadsOverTime":[],"referenceCount":0,"citationCount":0,"citationsOverTime":[],"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2016-01-18T21:01:32.000Z","registered":"2016-01-18T21:01:34.000Z","published":"2015","updated":"2020-09-05T00:16:00.000Z"},"relationships":{"client":{"data":{"id":"figshare.ars","type":"clients"}},"provider":{"data":{"id":"otjm","type":"providers"}},"media":{"data":{"id":"10.6084/m9.figshare.960499.v1","type":"media"}},"references":{"data":[]},"citations":{"data":[]},"parts":{"data":[]},"partOf":{"data":[]},"versions":{"data":[]},"versionOf":{"data":[]}}}}