title: [Multiple visualisation in data analysis: a ViSta application for principal component analysis].
abstract: Multiple visualisation (MV) is a statistic graphical method barely applied in data analysis practice, even though it provides interesting features for this purpose. This paper: (1) describes the application of the MV graphical method; (2) presents a number of rules related to the design of an MV; (3) introduces a general outline for developing MVs and shows how MV may be implemented in the ViSta statistical system; (4) illustrates this strategy by means of an example of MV oriented to principal component analysis; and, finally, (5) discusses some limitations of using and developing MVs.
authors.affiliation: CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas), Argentina.
authors.forename: Rubén
authors.initials: R
authors.lastname: Ledesma
authors.forename: J G
authors.initials: JG
authors.lastname: Molina
authors.forename: Forrest W
authors.initials: FW
authors.lastname: Young
authors.forename: Pedro
authors.initials: P
authors.lastname: Valero-Mora
mesh_terms: D003196:Computer Graphics / Q000295:instrumentation*; D003627:Data Interpretation, Statistical; D006801:Humans; D011584:Psychology / Q000295:instrumentation / Q000379:methods*; D012984:Software