summary.PTAk | R Documentation |
Print a summary listing of the decomposition obtained.
## S3 method for class 'PTAk'
summary(object,testvar=1,dontshow="*", ...)
## S3 method for class 'FCAk'
summary(object,testvar=0.5,dontshow="*", ...)
object |
an object inheriting from class |
testvar |
control within |
dontshow |
boolean criterion to remove Principal Tensors from the summary, or
default is a character "*" equivalent to the criterion:
|
... |
summary generic additional arguments not used here |
The function prints a listing of the decomposition with historical
order (instead of traditional singular value order). It is useful
before any plots or reconstruction, a screeplot (using
plot.PTAk
) will be also useful. It is useful before any plots
r reconstruction, a screeplot (using plot.PTAk
) will be also
useful. summary.FCAk
is alike
summary.PTAk
but testvar
operates on the variability of
the lack of complete independence.
prints on the prompt with an invisible return of the summary table
At the moment can be used for PCAn
,
CANDPRA
, better summaries will be in the next release.
Didier G. Leibovici GeotRYcs@gmail.com
Leibovici D (2000) Multiway Multidimensional Analysis for Pharmaco-EEG Studies.(submitted) https://www.researchgate.net/publication/216807619_Multiway_Multidimensional_Analysis_for_Pharmaco-EEG_Studies
plot.PTAk
data(crimerate)
crimerate.mat <- sweep(crimerate,2,apply(crimerate,2,mean))
crimerate.mat <- sweep(crimerate.mat,2,sqrt(apply(crimerate,2,var)),FUN="/")
cri.svd <- SVDgen(crimerate.mat)
summary(cri.svd,testvar=0)
plot(cri.svd,scree=TRUE)
par(new=TRUE)
RiskJackplot(cri.svd,nbvs=1:7,mod=NULL,max=NULL,rescaled=TRUE,
axes=FALSE,ann=FALSE)
par(new=FALSE)
# or equivalently
plot(cri.svd,scree=TRUE,type="b",lty=3,RiskJack=1) #set mod=NULL or c(1,2)
###
data(crimerate)
criafc <- FCAmet(crimerate,chi2=TRUE)
cri.afc <- SVDgen(criafc$data,criafc$met[[2]],criafc$met[[1]])
summary(cri.afc)
plot(cri.afc,scree=TRUE)
plot(cri.afc,scree=TRUE,type="b",lty=3,RiskJack=1,method="FCA")
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