I got a bunch dynamically created regressions stored in some list called regressions
. Now I´d like to rename their coefficients efficiently. What I have so far is this loop that works:
for (i in 1:length(params[,1])){
names(regressions[[i]]$coefficients)[pos] <- paste(params[i,1],".lag",params[i,2],sep="")
}
I've been trying for quite a while to get this done a little more generally with the help of a function, cause this not the only list of regressions I have. However I could not get anything else to work. Here a few other tries basically based on lapply:
correctNames <- function(reglist,namevec,pos){
names(reglist[[i]]$coefficients)[pos] <- as.character(namevec)
}
lapply(regressions,correctNames(reglist,namevec,pos),
reglist=regressions,namevec=params[,1],pos=2)
Another try was to write a function with a for loop开发者_C百科 which also works internally as print shows but does not assign the names globally (where the regressions list is stored).
correctNames <- function(reglist,pos,namevec){
for (i in 1:length(params[,1])){
names(reglist[[i]]$coefficients)[pos] <- paste(namevec,".lag",namevec,sep="")
}
#this test proves it's work inside the function...
print(reglist[[10]]
}
Ah, gimme a break.
There's no "i" inside that first version of "correctNames" function; and you probably don't realize that you are not assigning it to "regressions", only to a copy of the regression object. Try instead:
correctNames <- function(reglist,namevec,pos){
names(reglist$coefficients)[pos] <- as.character(namevec)
return(reglist) }
newregs <- mapply(correctNames,
reglist=regressions,
namevec=as.character(params[,1]),
MoreArgs= list( pos=2))
After seeing the note from Ramnath and noticing that the code did work but was giving flaky names for the "params" I looked at params and saw that it was a factor, and so changed the argument in the mapply
call to as.character(params[,1])
.
> newregs[1,1]
[[1]]
(Intercept) log(M1)
-5.753758 2.178137
If this is a follow up to your earlier question, then here is what I would do
coefs = plyr::ldply(regressions, coef)
coefs = transform(coefs, reg_name = paste(x, '.lag', l, sep = ""))[,-c(1, 2)]
names(coefs) = c('intercept', 'reg_coef', 'reg_name')
This gives you
intercept reg_coef reg_name
1 -5.753758 2.178137 log(M1).lag0
2 7.356434 7.532603 rs.lag0
3 7.198149 8.993312 rl.lag0
4 -5.840754 2.193382 log(M1).lag1
5 7.366914 7.419599 rs.lag1
6 7.211223 8.879969 rl.lag1
7 -5.988306 2.220994 log(M1).lag4
8 7.395494 7.127231 rs.lag4
9 7.246161 8.582998 rl.lag4
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