自动将R代码转换为Matlab

时间：2018-06-27 15:33:46

标签： r matlab

我想将此代码从R转换为Matlab。

require(tseries)
require(fracdiff)
require(matrixStats)

DCCA_beta_avg<-function(y,x,smin,smax,step){
  XTX<-var(x)*(length(x)-1)
  betas<-rep(0,(smax-smin)/step+1)
  for(s in seq(smin,smax,by=step)){
    betas[(s-smin)/step+1]<-DCCA_beta_sides(y,x,s)
  }
  DCCA_beta<-mean(betas)
  DCCA_res<-(y-DCCA_beta*x)-mean(y-DCCA_beta*x)
  DCCA_sigma2<-sum(DCCA_res^2)/(length(DCCA_res)-2)
  DCCA_SE<-sqrt(DCCA_sigma2/XTX)
  DCCA_R2<-1-var(DCCA_res)/var(y)
  OLS_beta<-lm(y~x)$coefficients[2]
  OLS_res<-(y-OLS_beta*x)-mean(y-OLS_beta*x)
  OLS_sigma2<-sum(OLS_res^2)/(length(OLS_res)-2)
  OLS_SE<-sqrt(OLS_sigma2/XTX)
  OLS_R2<-1-var(OLS_res)/var(y)
  return(c(OLS_beta,OLS_SE,OLS_R2,DCCA_beta,DCCA_SE,DCCA_R2))
}

DCCA_beta<-DCCdccafunction(y,x,s){
  xx<-cumsum(x-mean(x))
  yy<-cumsum(y-mean(y))
  t<-1:length(xx)
  F2sj_xy<-runif(floor(length(xx)/s))
  F2sj_xx<-F2sj_xy
  for(ss in seq(1,(floor(length(xx)/s)*s),by=s)){
    F2sj_xy[(ss-1)/s+1]<-sum((summary(lm(xx[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals)*(summary(lm(yy[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals))/(s-1)
    F2sj_xx[(ss-1)/s+1]<-sum((summary(lm(xx[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals)*(summary(lm(xx[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals))/(s-1)
  }
  beta<-mean(F2sj_xy)/mean(F2sj_xx)
  return(beta)
}

DCCA_beta_F<-function(y,x,s){
  xx<-cumsum(x-mean(x))
  yy<-cumsum(y-mean(y))
  t<-1:length(xx)
  F2sj_xy<-runif(floor(length(xx)/s))
  F2sj_xx<-F2sj_xy
  F2sj_yy<-F2sj_xy
  for(ss in seq(1,(floor(length(xx)/s)*s),by=s)){
    F2sj_xy[(ss-1)/s+1]<-sum((summary(lm(xx[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals)*(summary(lm(yy[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals))/(s-1)
    F2sj_xx[(ss-1)/s+1]<-sum((summary(lm(xx[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals)*(summary(lm(xx[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals))/(s-1)
    F2sj_yy[(ss-1)/s+1]<-sum((summary(lm(yy[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals)*(summary(lm(yy[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals))/(s-1)
  }
  beta<-mean(F2sj_xy)/mean(F2sj_xx)
  return(c(beta,mean(F2sj_xx),mean(F2sj_yy)))
  #return(c(beta,sum(F2sj_xx),sum(F2sj_yy)))
}

DCCA_beta_SE<-function(y,x,s){
  r<-DCCA_beta_F(y,x,s)
  beta<-r[1]
  yhat<-beta*x
  alpha<-mean(y)-beta*mean(x)
  res<-y-yhat
  residuals<-res-mean(res)
  resres<-cumsum(residuals-mean(residuals))
  F2sj_res<-runif(floor(length(residuals)/s))
  t<-1:length(resres)
  for(ss in seq(1,(floor(length(residuals)/s)*s),by=s)){
    F2sj_res[(ss-1)/s+1]<-sum((summary(lm(resres[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals)*(summary(lm(resres[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals))/(s-1)
  }
  #SE<-mean(residuals^2)/((length(residuals)-2)*r[2])
  SE<-mean(F2sj_res)/((length(residuals)-2)*r[2])
  SE_a<-(mean(F2sj_res)/r[2])*(sum(x^2)/(length(residuals)*(length(residuals)-2)))
  R<-1-mean(F2sj_res)/(r[3])
  return(c(alpha,sqrt(SE_a),beta,sqrt(SE),R))
}

DCCA_beta_SE_F<-function(y,x,s){
  r<-DCCA_beta_F(y,x,s)
  beta<-r[1]
  yhat<-beta*x
  alpha<-mean(y)-beta*mean(x)
  res<-y-yhat
  residuals<-res-mean(res)
  res_R<-y-x
  resres<-cumsum(residuals-mean(residuals))
  resres_R<-cumsum(res_R)
  F2sj_res<-runif(floor(length(residuals)/s))
  F2sj_res_R<-runif(floor(length(res_R)/s))
  t<-1:length(resres)
  for(ss in seq(1,(floor(length(residuals)/s)*s),by=s)){
    F2sj_res[(ss-1)/s+1]<-sum((summary(lm(resres[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals)*(summary(lm(resres[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals))/(s-1)
    F2sj_res_R[(ss-1)/s+1]<-sum((summary(lm(resres_R[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals)*(summary(lm(resres_R[ss:(ss+s-1)]~t[ss:(ss+s-1)]))$residuals))/(s-1)
  }
  #SE<-mean(residuals^2)/((length(residuals)-2)*r[2])
  #SE<-mean(F2sj_res)/((length(residuals)-2)*r[2])
  #SE<-mean(F2sj_res)/((length(F2sj_res)-2)*r[2]) #controlling for uncertainty connected to scales (higher scales have higher uncertainty due to lower number of blocks)
  SE<-mean(F2sj_res)/(ceiling(length(residuals)/s)*r[2]) #loosing d.f. due to fitting a and b in each box
  #SE_a<-(mean(F2sj_res)/r[2])*(sum(x^2)/(length(residuals)*(length(residuals)-2)))
  #SE_a<-(mean(F2sj_res)/r[2])*(sum(x^2)/(length(F2sj_res)*(length(F2sj_res)-2))) #controlling for uncertainty connected to scales (higher scales have higher uncertainty due to lower number of blocks)
  SE_a<-(mean(F2sj_res)/r[2])*(sum(x^2)/(length(residuals)*ceiling(length(residuals)/s))) #loosing d.f. due to fitting a and b in each box
  R<-1-mean(F2sj_res)/(r[3])
  #SSR_U<-sum(residuals^2)
  SSR_U<-sum(F2sj_res)
  #SSR_R<-sum((y-x)^2) #specific null: alpha=0, beta=1
  SSR_R<-sum(F2sj_res_R)
  #F_stat<-((SSR_R-SSR_U)/(SSR_U))*((length(residuals)-2)/2)
  #F_stat<-((SSR_R-SSR_U)/(SSR_U))*((length(F2sj_res)-2)/2) #controlling for uncertainty connected to scales (higher scales have higher uncertainty due to lower number of blocks)
  F_stat<-((SSR_R-SSR_U)/(SSR_U))*(ceiling(length(residuals)/s)/2) #loosing d.f. due to fitting a and b in each box
  F_p<-pf(F_stat,2,length(F2sj_res)-2,lower.tail=FALSE)
  return(c(alpha,sqrt(SE_a),beta,sqrt(SE),R,F_stat,F_p))
}

DCCA_beta_s<-function(y,x,smin,smax,step){
  results<-matrix(rep(0,6*((smax-smin)/step+1)),ncol=6)
  for(s in seq(smin,smax,by=step)){
    beta<-DCCA_beta_SE(y,x,s)
    results[((s-smin)/step+1),1]<-s
    results[((s-smin)/step+1),2]<-beta[1]
    results[((s-smin)/step+1),3]<-beta[2]
    results[((s-smin)/step+1),4]<-beta[3]
    results[((s-smin)/step+1),5]<-beta[4]
    results[((s-smin)/step+1),6]<-beta[5]
  }
  return(results)
}

DCCA_beta_s_F<-function(y,x,smin,smax,step){
  results<-matrix(rep(0,10*((smax-smin)/step+2)),ncol=10)
  for(s in seq(smin,smax,by=step)){
    beta<-DCCA_beta_SE_F(y,x,s)
    results[((s-smin)/step+1),1]<-s
    results[((s-smin)/step+1),2]<-beta[1]
    results[((s-smin)/step+1),3]<-beta[2]
    results[((s-smin)/step+1),4]<-2*pnorm(abs(beta[1]/beta[2]),lower.tail=FALSE)#p-value for null=0
    results[((s-smin)/step+1),5]<-beta[3]
    results[((s-smin)/step+1),6]<-beta[4]
    results[((s-smin)/step+1),7]<-2*pnorm(abs((beta[3]-1)/beta[4]),lower.tail=FALSE)#p-value for null=1
    results[((s-smin)/step+1),8]<-beta[5]
    results[((s-smin)/step+1),9]<-beta[6]
    results[((s-smin)/step+1),10]<-beta[7]
  }
  #results[(smax-smin)/step+2,2]<-mean(results[1:(dim(results)[1]-1),2])#A
  #results[(smax-smin)/step+2,5]<-mean(results[1:(dim(results)[1]-1),5])#B
  results[(smax-smin)/step+2,2]<-sum(results[1:(dim(results)[1]-1),2]*results[1:(dim(results)[1]-1),8])/sum(results[1:(dim(results)[1]-1),8])#A as R2(s) weighted
  results[(smax-smin)/step+2,5]<-sum(results[1:(dim(results)[1]-1),5]*results[1:(dim(results)[1]-1),8])/sum(results[1:(dim(results)[1]-1),8])#B as R2(s) weighted
  results[(smax-smin)/step+2,3]<-sqrt((sum(x^2)/length(x))*sum((y-results[(smax-smin)/step+2,2]-results[(smax-smin)/step+2,5]*x)^2)/((length(y)-dim(results)[1]+1)*sum((x-mean(x))^2)))#SE_A
  results[(smax-smin)/step+2,4]<-2*pnorm(abs(results[(smax-smin)/step+2,2]/results[(smax-smin)/step+2,3]),lower.tail=FALSE)#p-value for null=0
  results[(smax-smin)/step+2,6]<-sqrt(sum((y-results[(smax-smin)/step+2,2]-results[(smax-smin)/step+2,5]*x)^2)/((length(y)-dim(results)[1]+1)*sum((x-mean(x))^2)))#SE_B
  results[(smax-smin)/step+2,7]<-2*pnorm(abs((results[(smax-smin)/step+2,5]-1)/results[(smax-smin)/step+2,6]),lower.tail=FALSE)#p-value for null=1
  results[(smax-smin)/step+2,8]<-1-sum((y-results[(smax-smin)/step+2,2]-results[(smax-smin)/step+2,5]*x)^2)/sum(y^2)#R2
  results[(smax-smin)/step+2,9]<-((length(x)-2)/2)*((results[(smax-smin)/step+2,8]-(1-(sum((y-x)^2))/(sum((y-mean(y))^2))))/(1-results[(smax-smin)/step+2,8]))#F_test_R2_based
  results[(smax-smin)/step+2,10]<-pf(results[(smax-smin)/step+2,9],2,length(y)-2,lower.tail=FALSE)#F_test p_val
  return(results)
}

这旨在执行回归参数的计算以及去趋势的互相关分析。

有没有一种自动执行此操作的方法？或者我们应该一行一行地做。

此分析应在相同长度的time series上进行。

1 个答案:

答案 0 :(得分：1)

答案是否定的，或者至少我不知道有什么办法，因为它们是两种不同的语言。

也许您想查看Matlab中的文件交换，有一个类似MATLAB R-link的脚本可以让您将Matlab与R连接起来，这样您就可以在R中调用MatLab的函数。

这是此文件的描述：

  

基于COM的接口，允许您从MATLAB内调用R函数。这些功能是：

     

openR-连接到R服务器进程。

     

evalR-运行R命令。

     

getRdata-将R变量复制到MATLAB。

     

putRdata-将MATLAB数据复制到R变量。

     

closeR-关闭与R服务器进程的连接。

     

Rdemo-在MATLAB中使用R的示例。

另一种选择是您逐行翻译代码。

编辑： 我一直在搜索更多选项，发现this one允许将r代码执行到Matlab

希望这对您有所帮助。

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