R: 'DiStatis' of a DiStatis object High level constructor of...
DiStatis
R Documentation
DiStatis of a DiStatis object
High level constructor of DiStatis class object
Description
This is the function that makes DiStatis Methodology: Statis is part of the PCA
family and therefore the main analytical tool for STATIS
is the singular value decomposition (SVD) and the
generalized singular value decomposition (GSVD) of a matrix.
The goal of Statis is to analyze several data sets of
variables that were collected on the same set of observations.
Originally, the comparisons were drawn from the compute
of the scalar product between the different tables.
In this approach, the condition is made more flexible,
allowing the incorporation of different distance measurements
(including the scalar product) to compare the tables.
function to do Statis (K-tables methodology)with distance options
The data frame or of k-tables type. The Observations should be in rows (common elements in DAnisostatis), the variables and Studies must be in columns. After the name of the variable an underscore (_) must be written to indicate the Study (eg. Var1_Est1 , eg. Var1_EstK, for more information see the data object). The name of a variable can include any symbol except an underscore (_). REMEMBER the underscore (_) should be reserved to indicate the study.
Also, the Data can be a list of k components.
Each element of the list is one of the tables
with observations in rows and variables in columns.
The elements of list must be data.frame or ExpressionSet data.
Distance
Vector is the length equal to the number of studies
that indicates the kind of distance (or scalar product)
that is calculated in each study. If not specify
(or is wrong specify) the scalar product is used.
The options can be ScalarProduct, euclidean,
manhattan, canberra, pearson, pearsonabs, spearman,
spearmanabs, mahalanobis. In the binary data the distance can be: jaccard,
simple matching, sokal&Sneath, Roger&Tanimoto, Dice,
Hamman,#' Ochiai, Sokal&Sneath, Phi-Pearson,
Gower&Legendre.
Center
A logical value. If TRUE, the data frame
is centered by the mean. By default is TRUE.
Scale
A logical value indicating whether the column vectors (of the data.frame) should be
standardized by the rows weight, by default is TRUE.
CorrelVector
a logical value. If TRUE (default), Vectorial correlation coefficient is computed for the RV matrix.
If FALSE the Hilbert-Smith distance is used in the RV matrix.
Frec
Logical. Should the data be treated data as frequencies? By default is FALSE.
Traj
Logical. Should the trajectories analysis be done? By default is TRUE.
Format
An object of class NULL of length 0.
Details
STATIS methods: to more information, see references.
Value
DiStatis
DiStatis class object with the
corresponding completed slots
according to the given model
Note
use DiStatis-class high level
constructor for the
creation of the class instead of directly
calling its constructor by new
means.
Author(s)
M L Zingaretti, J A Demey-Zambrano, J L Vicente Villardon, J R Demey
References
Abdi, H., Williams, L.J.,
Valentin, D., & Bennani-Dosse, M. (2012).
STATIS and DISTATIS: optimum multitable principal
component analysis and three way metric multidimensional scaling.
WIREs Comput Stat, 4, 124-167.
Escoufier, Y. (1976). Operateur associe a un tableau de donnees. Annales de laInsee, 22-23, 165-178.
Escoufier, Y. (1987). The duality diagram: a means for better practical applications. En P. Legendre & L. Legendre (Eds.), Developments in Numerical Ecology, pp. 139-156, NATO Advanced Institute, Serie G. Berlin: Springer.
L'Hermier des Plantes, H. (1976). Structuration des Tableaux a Trois Indices de la Statistique. [These de Troisieme Cycle]. University of Montpellier, France.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(kimod)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/kimod/DiStatis-DiStatis.Rd_%03d_medium.png", width=480, height=480)
> ### Name: DiStatis
> ### Title: 'DiStatis' of a DiStatis object High level constructor of
> ### DiStatis class object
> ### Aliases: DiStatis DiStatis-methods
> ### Keywords: datasets
>
> ### ** Examples
>
> {
+ data(NCI60Selec_ESet)
+ Z1<-DiStatis(NCI60Selec_ESet)
+ data(winesassesors)
+ Z3<-DiStatis(winesassesors)
+
+ }
The calculations were performed using the scalar product between the tables
The Projection of all variables will be made when the number of variables is less than 50
The calculations were performed using the scalar product between the tables
The Projection of all variables will be made when the number of variables is less than 50
>
>
>
>
>
>
> dev.off()
null device
1
>