moa-class: Class '"moa"'

Description Objects from the Class Slots Methods Author(s) References Examples

Description

moa class object

Objects from the Class

Objects can be created by calls of the form new("moa", ...).

Slots

eig:

eigen values

tau:

The percentage of explained variance by each datasets sparately.

partial.eig:

matrix, rows indicate the partial eigenvalues from each data.

eig.vec:

a matrix, eigenvectors.

loading:

the coordinate of variables/features.

fac.scr:

factor score of observations.

partial.fs:

partial factor score.

ctr.obs:

contribution of each observation to the total factor score.

ctr.var:

contribution of each variables to the total variance.

ctr.tab:

contribution of each data to the total variance.

RV:

pairwise RV coefficients

w.row:

weight of rows

w.data:

weight of datasets

data:

the original input data

tab.dim:

the dimension of each input data

call:

call

Methods

plot

signature(x = "moa", y = "missing"): Argument "value" sould be one of "eig", "tau", "obs", "var" and "RV"

if value = "eig", the eigenvalue would be plotted as scree plot. The following arguments could be set:

type=1 - The type of plot to show eigenvalues. (type=1: the eigenvalue are plotted; type=2: partial eigenvalue shown as concatenated bars; type=3: partial eigenvalue shown as bars side by side; type=4: matplot view of eigenvales, lty need to be set; type=5; the two dimensional plot of partial eigenvalues, axes and pch need to be set in this case.)

axes=NULL - The axes selected to plot

n=NULL - Top n eigenvalues to be drawn

tol=1e-5 - The tolerance of eigenvalue, eigenvalues lower than this value will not be shown.

legend=NULL - legend to put, a character string as calling legend function

col=NULL - The color of partial eigenvalues from each data set

lty=1 - The line type used in the matplot, used when type =4

pch=NULL - the pch to draw 2D partial eigen plot, when type = 5 used

lg.x="topright" - The position of legend

lg.y=NULL - Poistion argument passed to function "legend"

... - other arguemnts passed to functions

if value = "tau", the same with eig, but in the eigenvalues are scaled to 1

if value = "obs", the observation space will be shown, the following argument could be set:

axes=1:2 - Which axes should be draw

type=1 - Which type, see below (for type=1: the center points draw; type=2: the separate factor scores linked by lines; ... will be passed to function "points")

data.pch=20 - the pch of dataset, if type=1, the first one is used

col=1 - the color of observations, recycled used by data.frame

label=FALSE - A logical indicates if labels should be shown

lg.x="topright" - Position of legend

lg.y=NULL - Position of legend

xlim=NULL - The x limit

ylim=NULL - The y limit

label.cex=1 - the cex of text

...

var - the separate gene view, layout can be specified

RV - the heatmap of RV coefficients

show

signature(x = "moa", y = "missing"): show "moa" object

Author(s)

Chen Meng

References

Herve Abdi, Lynne J. Williams, Domininique Valentin and Mohammed Bennani-Dosse. STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling. WIREs Comput Stat 2012. Volume 4, Issue 2, pages 124-167

Herve Abdi, Lynne J. Williams, Domininique Valentin. Multiple factor analysis: principal component analysis for multitable and multiblock data sets. WIREs Comput Stat 2013

Examples

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    showClass("moa")
    # load("R/mogsa/data/NCI60_4arrays.rda")
    data(NCI60_4arrays)
    ana <- moa(NCI60_4arrays, proc.row = "center_ssq1", w.data = "inertia", statis = TRUE)

    plot(ana, value="eig")
    plot(ana, value="tau", type=2)

mengchen18/mogsa documentation built on Nov. 23, 2017, 1:57 a.m.