cvle-class {MetabolicSurv} | R Documentation |
The cvle Class.
Description
The cvle Class.
Slots
Coef.mat
A matrix of coefficients with rows equals to number of cross validations and columns equals to number of metabolites.
Runtime
A vector of runtime for each iteration measured in seconds.
lambda
A vector of estimated optimum lambda for each iterations.
n
A vector of the number of selected metabolites
Met.mat
A matrix with 0 and 1. Number of rows equals to number of iterations and number of columns equals to number of metabolites. 1 indicates that the particular metabolite was selected or had nonzero coefficient and otherwise it is zero.
HRTrain
A matrix of survival information for the training dataset. It has three columns representing the estimated HR, the 95% lower confidence interval and the 95% upper confidence interval.
HRTest
A matrix of survival information for the test dataset. It has three columns representing the estimated HR, the 95% lower confidence interval and the 95% upper confidence interval.
pld
A vector of partial likelihood deviance at each cross validations.
Mdata
The metabolite matrix that was used for the analysis which can either be the full the full data or a reduced supervised PCA version.
Author(s)
Olajumoke Evangelina Owokotomo, olajumoke.owokotomo@uhasselt.be
Ziv Shkedy
See Also
EstimateHR
, glmnet
, Lasoelacox
Examples
## GENERATE SOME METABOLIC SURVIVAL DATA WITH PROGNOSTIC FACTORS
Data<-MSData(nPatients=100,nMet=150,Prop=0.5)
## USE THE FUNCTION
Eg = CVLasoelacox(Survival = Data$Survival,Censor = Data$Censor,
Mdata = t(Data$Mdata),Prognostic = Data$Prognostic, Quantile = 0.5,
Metlist = NULL,Standardize = TRUE, Reduce=FALSE, Select=15,
Alpha = 1,Fold = 4,Ncv = 10,nlambda = 100)
## GET THE CLASS OF THE OBJECT
class(Eg) # An "cvle" Class
## METHOD THAT CAN BE USED FOR THIS CLASS
show(Eg)
summary(Eg)
plot(Eg, type =3)