Question

I have a mega data frame containing monthly stock returns from january 1970 to december 2009 (rows) for 7 different countries including the US (columns). My task is to regress the stock returns of each country (dependent variable) on the USA stock returns (independent variable) using the values of 4 different time periods namely the 70s, the 80s, the 90s and the 00s.

The data set (.csv) can be downloaded at:
https://docs.google.com/file/d/0BxaWFk-EO7tjbG43Yl9iQVlvazQ/edit

This means that I have 24 regressions to run seperately and report the results, which I have already done using the lm() function. However, I am currently attempting to use R smarter and create custom functions that will achieve my purpose and produce the 24 sets of results.

I have created sub data frames containing the observations clustered according to the time periods knowing that there are 120 months in a decade.

seventies = mydata[1:120, ] # 1970s (from Jan. 1970 to Dec. 1979)
eighties = mydata[121:240, ] # 1980s (from Jan. 1980to Dec. 1989)
nineties = mydata[241:360, ] # 1990s (from Jan. 1990 to Dec. 1999)
twenties = mydata[361:480, ] # 2000s (from Jan. 2000 to Dec. 2009)

NB: Each of the newly created variables are 120 x 7 matrices for 120 observations across 7 countries.

Running the 24 regressions using Java would require the use of imbricated for loops.

Could anyone provide the steps I must take to write a function that will arrive a the desired result? Some snippets of R code would also be appreciated. I am also thinking the mapply function will be used.

Thank you and let me know if my post needs some editing.

Answer 1

try this:

 install.packages('plyr')
 library('plyr')
 myfactors<-c(rep("seventies",120),rep("eighties",120),rep("nineties",120),rep("twenties",120))
 tapply(y,myfactors,function(y,X){ fit<-lm(y~ << regressors go here>>; return (fit);},X=mydata)