我在做数据模拟的时候也遇到了这个问题，下面是我的程序，当我把变量个数设为5000时，程序就会报告：错误，无法分配大小为95.4M的矢量。这是怎么回事，我用了rm(),gc(),还是不管用啊,像这样应该怎么解决呢

rm(list=ls())

library(MASS)

library(stats)

library(utils)

library(graphics)

library(splines)

library(survival)

library(penalized)

library(MASS)

library(SIS)

library(lattice)

library(Matrix)

gendata <- function(n,cor,beta)

  {

        #design matrix

        X=mvrnorm(n,rep(0,p),cor)

        #observed survivial time

        #set.seed(seed+1000)

        logS=log(matrix(runif(n,0,1),n,1)) #log[S(t)]

        T=-logS/(exp(X%*%beta))

      #censored time

        C <- rexp(n, rate =0.1)

        #survival time and state

        time <- apply(cbind(C,T),1,min)

        stat <- as.numeric(T<C)

        #combin data

        return(list("X"=X,"surv"=Surv(time,stat),"time"=time,"stat"=stat))

}

n=100  #sample size

sample=2 #simulation times

#beta vector

beta1<-c(1.8762,-2.2746,1.9497,-1.9826,1.956277,-2.2077,1.9929,-2.4966,1.8992,-1.9458)

beta2<-rep(0,4990)

beta<-matrix(c(beta1,beta2))

beta11<-which(beta!=0)

p <- length(beta)

d <- p-length(beta[beta==0])

#generate correlation matrix ,第一种方案，相关系数为零，即个自变量间相互独立

cor=matrix(1,p,p)

for (i in 1:p)

{

        for (j in 1:p)

                {

               if(i!=j)

                 {

                cor[i,j]=0 #correlation matrix

                      }

            }

}

i=1

for (i in 1:sample){

if (i>1 ){rm(simcox,opt1pf,lambda,coxlasso,opt1,fit2,lambda22,fit1,lambda11,pen)

              gc()}#删除上一次循环中的结果，避免影响下一次

###############generate data

simcox <-gendata(n,cor,beta)

attach(simcox)

#Cox: lasso

opt1pf <- profL1(surv, penalized = X, fold = 10, data=simcox)

lambda <- opt1pf

lambda[opt1pfcvl==max(opt1pf$cvl)]

coxlasso <- penalized(surv, penalized = X, data=simcox, lambda1=lambda)

}