BIVARIATE QQ-PLOTS AND SPIDER WEB PLOTS
QQ-plots are extremely useful in univariate data analysis. In this article, Koltchinskii (1997) and Chaudhuri's (1996) definition of multivariate quantile is used to develop analogous plots for bivariate data. Bivariate qq-plots are exhibited for comparing a sample to a given population distrib...
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| Veröffentlicht in: | Statistica Sinica 1998-07, Vol.8 (3), p.813-826 |
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| creator | Marden, John I. |
| description | QQ-plots are extremely useful in univariate data analysis. In this article, Koltchinskii (1997) and Chaudhuri's (1996) definition of multivariate quantile is used to develop analogous plots for bivariate data. Bivariate qq-plots are exhibited for comparing a sample to a given population distribution (the bivariate normal), and for comparing two or more bivariate samples. The plots are based on drawing arrows from the quantiles in one distribution to the corresponding quantiles in the other. These plots can reveal differences in location, scale and skewness, as well as outliers. Spider web plots are introduced for plotting a systematic set of quantiles for a single sample without having to specify a reference population distribution. |
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In this article, Koltchinskii (1997) and Chaudhuri's (1996) definition of multivariate quantile is used to develop analogous plots for bivariate data. Bivariate qq-plots are exhibited for comparing a sample to a given population distribution (the bivariate normal), and for comparing two or more bivariate samples. The plots are based on drawing arrows from the quantiles in one distribution to the corresponding quantiles in the other. These plots can reveal differences in location, scale and skewness, as well as outliers. 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In this article, Koltchinskii (1997) and Chaudhuri's (1996) definition of multivariate quantile is used to develop analogous plots for bivariate data. Bivariate qq-plots are exhibited for comparing a sample to a given population distribution (the bivariate normal), and for comparing two or more bivariate samples. The plots are based on drawing arrows from the quantiles in one distribution to the corresponding quantiles in the other. These plots can reveal differences in location, scale and skewness, as well as outliers. Spider web plots are introduced for plotting a systematic set of quantiles for a single sample without having to specify a reference population distribution.</description><subject>Arithmetic mean</subject><subject>Baseball</subject><subject>Calyx</subject><subject>Distribution functions</subject><subject>Linear transformations</subject><subject>Population distributions</subject><subject>Quantiles</subject><subject>Robust and Nonparametric Multivariate Methods</subject><subject>Sampling distributions</subject><subject>Skewed distribution</subject><subject>Spider webs</subject><issn>1017-0405</issn><issn>1996-8507</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><sourceid/><recordid>eNotjE1rwzAQREVoICHJTyjo1pNgZe1qraOTuK3B5NNpj0GuJEhoabFz6b-vaXuaecNjRmKqnbMqJ-C7oYNmBQg0EYu-v7QADkjnYKbiYVm9FIeqaEq536tdvW2Ostis5XFXrcuDfC2X8neci3Hy731c_OdMnB7LZvWs6u1TtSpqddVMN2Wtodb55ChyCK5l32a5B44YXEKTZ8CY-A0IkG3QYQCKOAg2MTuMZibu_36v_e2zO391lw_ffZ8zNGDRkvkBzOA3FA</recordid><startdate>19980701</startdate><enddate>19980701</enddate><creator>Marden, John I.</creator><general>Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association</general><scope/></search><sort><creationdate>19980701</creationdate><title>BIVARIATE QQ-PLOTS AND SPIDER WEB PLOTS</title><author>Marden, John I.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-j175t-6635b9af95e7dd9b7ab28a07e4d9f4382074f7c050476d1d4f75e4a076f7794e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Arithmetic mean</topic><topic>Baseball</topic><topic>Calyx</topic><topic>Distribution functions</topic><topic>Linear transformations</topic><topic>Population distributions</topic><topic>Quantiles</topic><topic>Robust and Nonparametric Multivariate Methods</topic><topic>Sampling distributions</topic><topic>Skewed distribution</topic><topic>Spider webs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Marden, John I.</creatorcontrib><jtitle>Statistica Sinica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Marden, John I.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>BIVARIATE QQ-PLOTS AND SPIDER WEB PLOTS</atitle><jtitle>Statistica Sinica</jtitle><date>1998-07-01</date><risdate>1998</risdate><volume>8</volume><issue>3</issue><spage>813</spage><epage>826</epage><pages>813-826</pages><issn>1017-0405</issn><eissn>1996-8507</eissn><abstract>QQ-plots are extremely useful in univariate data analysis. In this article, Koltchinskii (1997) and Chaudhuri's (1996) definition of multivariate quantile is used to develop analogous plots for bivariate data. Bivariate qq-plots are exhibited for comparing a sample to a given population distribution (the bivariate normal), and for comparing two or more bivariate samples. The plots are based on drawing arrows from the quantiles in one distribution to the corresponding quantiles in the other. These plots can reveal differences in location, scale and skewness, as well as outliers. Spider web plots are introduced for plotting a systematic set of quantiles for a single sample without having to specify a reference population distribution.</abstract><pub>Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association</pub><tpages>14</tpages></addata></record> |
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| ispartof | Statistica Sinica, 1998-07, Vol.8 (3), p.813-826 |
| issn | 1017-0405 1996-8507 |
| language | eng |
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| source | JSTOR Mathematics & Statistics; JSTOR Archive Collection A-Z Listing; EZB-FREE-00999 freely available EZB journals |
| subjects | Arithmetic mean Baseball Calyx Distribution functions Linear transformations Population distributions Quantiles Robust and Nonparametric Multivariate Methods Sampling distributions Skewed distribution Spider webs |
| title | BIVARIATE QQ-PLOTS AND SPIDER WEB PLOTS |
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