Improving my OLS Rolling Regression with lapply









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This is the code of my rolling regression:



# betas from rolling regression will be in betas_rolling_250 matrix
fixed.window<-30
models<-c("A~B+E","A~B+C","A~B+D","A~B+C","A~B+F","A~B+B","A~B+F","A~B+C")
betas_rolling_250<-matrix(,nrow=length(models),ncol=250-fixed.window)
rownames(betas_rolling_250)<-models;

#Sample Matrix

sample_matrix_250<-matrix(rexp(10, rate=.1),nrow=250, ncol=6)
colnames(sample_matrix_250)<-c("A","B","C","D","E","F")

for(i in 1:(length(sample_matrix_250[,1])-fixed.window))
for(k in 1:length(rownames(betas_rolling_250)))
coefs<-lm(rownames(betas_rolling_250)[k],data=as.data.frame(sample_matrix_250[(221-i):(251-i),]))$coefficients[3]
betas_rolling_250[k,i]<-coefs



First question:



Is it possible to implement this by using lapply function?



I am asking this beacause I will have to do this 4 times. Because I have more 4 differents size dataframes: (sample_matrix_220, sample_matrix_200and sample_matrix_180). I dont want my code to be huge.



Ive been thinking in using list. Thats why I though about lapply function.



Is it possible?










share|improve this question





















  • zoo::rollapply is probably convenient
    – Richard Telford
    Nov 11 at 15:32














up vote
0
down vote

favorite












This is the code of my rolling regression:



# betas from rolling regression will be in betas_rolling_250 matrix
fixed.window<-30
models<-c("A~B+E","A~B+C","A~B+D","A~B+C","A~B+F","A~B+B","A~B+F","A~B+C")
betas_rolling_250<-matrix(,nrow=length(models),ncol=250-fixed.window)
rownames(betas_rolling_250)<-models;

#Sample Matrix

sample_matrix_250<-matrix(rexp(10, rate=.1),nrow=250, ncol=6)
colnames(sample_matrix_250)<-c("A","B","C","D","E","F")

for(i in 1:(length(sample_matrix_250[,1])-fixed.window))
for(k in 1:length(rownames(betas_rolling_250)))
coefs<-lm(rownames(betas_rolling_250)[k],data=as.data.frame(sample_matrix_250[(221-i):(251-i),]))$coefficients[3]
betas_rolling_250[k,i]<-coefs



First question:



Is it possible to implement this by using lapply function?



I am asking this beacause I will have to do this 4 times. Because I have more 4 differents size dataframes: (sample_matrix_220, sample_matrix_200and sample_matrix_180). I dont want my code to be huge.



Ive been thinking in using list. Thats why I though about lapply function.



Is it possible?










share|improve this question





















  • zoo::rollapply is probably convenient
    – Richard Telford
    Nov 11 at 15:32












up vote
0
down vote

favorite









up vote
0
down vote

favorite











This is the code of my rolling regression:



# betas from rolling regression will be in betas_rolling_250 matrix
fixed.window<-30
models<-c("A~B+E","A~B+C","A~B+D","A~B+C","A~B+F","A~B+B","A~B+F","A~B+C")
betas_rolling_250<-matrix(,nrow=length(models),ncol=250-fixed.window)
rownames(betas_rolling_250)<-models;

#Sample Matrix

sample_matrix_250<-matrix(rexp(10, rate=.1),nrow=250, ncol=6)
colnames(sample_matrix_250)<-c("A","B","C","D","E","F")

for(i in 1:(length(sample_matrix_250[,1])-fixed.window))
for(k in 1:length(rownames(betas_rolling_250)))
coefs<-lm(rownames(betas_rolling_250)[k],data=as.data.frame(sample_matrix_250[(221-i):(251-i),]))$coefficients[3]
betas_rolling_250[k,i]<-coefs



First question:



Is it possible to implement this by using lapply function?



I am asking this beacause I will have to do this 4 times. Because I have more 4 differents size dataframes: (sample_matrix_220, sample_matrix_200and sample_matrix_180). I dont want my code to be huge.



Ive been thinking in using list. Thats why I though about lapply function.



Is it possible?










share|improve this question













This is the code of my rolling regression:



# betas from rolling regression will be in betas_rolling_250 matrix
fixed.window<-30
models<-c("A~B+E","A~B+C","A~B+D","A~B+C","A~B+F","A~B+B","A~B+F","A~B+C")
betas_rolling_250<-matrix(,nrow=length(models),ncol=250-fixed.window)
rownames(betas_rolling_250)<-models;

#Sample Matrix

sample_matrix_250<-matrix(rexp(10, rate=.1),nrow=250, ncol=6)
colnames(sample_matrix_250)<-c("A","B","C","D","E","F")

for(i in 1:(length(sample_matrix_250[,1])-fixed.window))
for(k in 1:length(rownames(betas_rolling_250)))
coefs<-lm(rownames(betas_rolling_250)[k],data=as.data.frame(sample_matrix_250[(221-i):(251-i),]))$coefficients[3]
betas_rolling_250[k,i]<-coefs



First question:



Is it possible to implement this by using lapply function?



I am asking this beacause I will have to do this 4 times. Because I have more 4 differents size dataframes: (sample_matrix_220, sample_matrix_200and sample_matrix_180). I dont want my code to be huge.



Ive been thinking in using list. Thats why I though about lapply function.



Is it possible?







r lapply






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asked Nov 11 at 14:42









Diogo Bastos

434313




434313











  • zoo::rollapply is probably convenient
    – Richard Telford
    Nov 11 at 15:32
















  • zoo::rollapply is probably convenient
    – Richard Telford
    Nov 11 at 15:32















zoo::rollapply is probably convenient
– Richard Telford
Nov 11 at 15:32




zoo::rollapply is probably convenient
– Richard Telford
Nov 11 at 15:32












1 Answer
1






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oldest

votes

















up vote
1
down vote













Consider generalizing your setup by passing the only changed variable, matrix column size, as input parameter. Then, past list of numeric values into an lapply call.



Below replaces any 250 to a variable (adjust as needed). The static models and fixed.window should be assigned once outside the function.



get_coeffs <- function(mat_size) 
betas_rolling <- matrix(,nrow=length(models), ncol=mat_size-fixed.window)
rownames(betas_rolling) <- models

sample_matrix <- matrix(rexp(10, rate=.1), nrow=mat_size, ncol=6)
colnames(sample_matrix) <- LETTERS[1:6]

for(i in 1:(length(sample_matrix[,1])-fixed.window))
for(k in 1:length(rownames(betas_rolling)))
coefs <- lm(rownames(betas_rolling)[k],
as.data.frame(sample_matrix[(mat_size-fixed.window)-i):(mat_size+1-i),]))$coefficients[3]
betas_rolling[k,i] <- coefs



return(betas_rolling)


matrix_list <- lapply(c(180, 200, 220, 250), get_coeffs)





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    up vote
    1
    down vote













    Consider generalizing your setup by passing the only changed variable, matrix column size, as input parameter. Then, past list of numeric values into an lapply call.



    Below replaces any 250 to a variable (adjust as needed). The static models and fixed.window should be assigned once outside the function.



    get_coeffs <- function(mat_size) 
    betas_rolling <- matrix(,nrow=length(models), ncol=mat_size-fixed.window)
    rownames(betas_rolling) <- models

    sample_matrix <- matrix(rexp(10, rate=.1), nrow=mat_size, ncol=6)
    colnames(sample_matrix) <- LETTERS[1:6]

    for(i in 1:(length(sample_matrix[,1])-fixed.window))
    for(k in 1:length(rownames(betas_rolling)))
    coefs <- lm(rownames(betas_rolling)[k],
    as.data.frame(sample_matrix[(mat_size-fixed.window)-i):(mat_size+1-i),]))$coefficients[3]
    betas_rolling[k,i] <- coefs



    return(betas_rolling)


    matrix_list <- lapply(c(180, 200, 220, 250), get_coeffs)





    share|improve this answer
























      up vote
      1
      down vote













      Consider generalizing your setup by passing the only changed variable, matrix column size, as input parameter. Then, past list of numeric values into an lapply call.



      Below replaces any 250 to a variable (adjust as needed). The static models and fixed.window should be assigned once outside the function.



      get_coeffs <- function(mat_size) 
      betas_rolling <- matrix(,nrow=length(models), ncol=mat_size-fixed.window)
      rownames(betas_rolling) <- models

      sample_matrix <- matrix(rexp(10, rate=.1), nrow=mat_size, ncol=6)
      colnames(sample_matrix) <- LETTERS[1:6]

      for(i in 1:(length(sample_matrix[,1])-fixed.window))
      for(k in 1:length(rownames(betas_rolling)))
      coefs <- lm(rownames(betas_rolling)[k],
      as.data.frame(sample_matrix[(mat_size-fixed.window)-i):(mat_size+1-i),]))$coefficients[3]
      betas_rolling[k,i] <- coefs



      return(betas_rolling)


      matrix_list <- lapply(c(180, 200, 220, 250), get_coeffs)





      share|improve this answer






















        up vote
        1
        down vote










        up vote
        1
        down vote









        Consider generalizing your setup by passing the only changed variable, matrix column size, as input parameter. Then, past list of numeric values into an lapply call.



        Below replaces any 250 to a variable (adjust as needed). The static models and fixed.window should be assigned once outside the function.



        get_coeffs <- function(mat_size) 
        betas_rolling <- matrix(,nrow=length(models), ncol=mat_size-fixed.window)
        rownames(betas_rolling) <- models

        sample_matrix <- matrix(rexp(10, rate=.1), nrow=mat_size, ncol=6)
        colnames(sample_matrix) <- LETTERS[1:6]

        for(i in 1:(length(sample_matrix[,1])-fixed.window))
        for(k in 1:length(rownames(betas_rolling)))
        coefs <- lm(rownames(betas_rolling)[k],
        as.data.frame(sample_matrix[(mat_size-fixed.window)-i):(mat_size+1-i),]))$coefficients[3]
        betas_rolling[k,i] <- coefs



        return(betas_rolling)


        matrix_list <- lapply(c(180, 200, 220, 250), get_coeffs)





        share|improve this answer












        Consider generalizing your setup by passing the only changed variable, matrix column size, as input parameter. Then, past list of numeric values into an lapply call.



        Below replaces any 250 to a variable (adjust as needed). The static models and fixed.window should be assigned once outside the function.



        get_coeffs <- function(mat_size) 
        betas_rolling <- matrix(,nrow=length(models), ncol=mat_size-fixed.window)
        rownames(betas_rolling) <- models

        sample_matrix <- matrix(rexp(10, rate=.1), nrow=mat_size, ncol=6)
        colnames(sample_matrix) <- LETTERS[1:6]

        for(i in 1:(length(sample_matrix[,1])-fixed.window))
        for(k in 1:length(rownames(betas_rolling)))
        coefs <- lm(rownames(betas_rolling)[k],
        as.data.frame(sample_matrix[(mat_size-fixed.window)-i):(mat_size+1-i),]))$coefficients[3]
        betas_rolling[k,i] <- coefs



        return(betas_rolling)


        matrix_list <- lapply(c(180, 200, 220, 250), get_coeffs)






        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 11 at 15:50









        Parfait

        48.5k84168




        48.5k84168



























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