[R] For loop question
I have this code:
IEF <- to.monthly(IEF, indexAt="endof")
SPY <- to.monthly(SPY, indexAt="endof")
I would like to use a for loop instead of separate entries,
so the only code that needs to be modified is the list
of symbols.
symbols <- c("IEF", "SPY")
for(symbol in symbols) {
symbol <- to.monthly(symbol, indexAt="endof")
}
This for loop doesn't work. It puts each output into
*symbol *not into *IEF *and *SPY*.
How do I put the output into the existing objects using
a for loop?
Note: to.monthly() is an xts function
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Re: [R] For loop question
Thanks. That got me the answer. This works:
symbols = c("IEF","SPY")
getSymbols(symbols)
for(symbol in symbols) {
assign(symbol, to.monthly(get(symbol), indexAt="endof"))
}
#end
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[R] Lasso for k-subset regression
Dear R-users I'm trying to use lasso in lars package for subset regression, I have a large matrix of size 1000x100 and my aim is to select a subset k of the 100 variables. Is there any way in lars to fix the number k (i.e. to select the best 10 variables) library(lars) aa=lars(X,Y,type="lasso",max.steps=200) plot(aa,plottype="Cp") aa$RSS which.min(aa$RSS) round(aa$beta,2) aa$beta[which.min(aa$RSS),]# find which coefficients minimizes the RSS lasso.ind=which((as.vector((aa$beta[which.min(aa$RSS),])))>0)# index of variables print(lasso.ind) # this usually gives more than 10 variables (also depends on the max.steps in lars) Thanks in advance [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] optim with simulated annealing SANN for combinatorial optimization
Hi all
I am trying to solve a combinatorial optimization problem. Basically, I can
reduce my problem into the next problem:
1.- Given a NxN grid of points, with some values in each cell
2.- Find the combination of K points on the grid such that, the maximum
mean value is obtained
I took the Travel SalesMan problem example in ?optim documentation. I am
not sure if I have understood correctly the SANN implementation in optim,
as I do not see how the acceptance probability comes out. And it looks like
I am only evaluating the criteria several times and keep the maximum at the
end.
Thanks in advance
Here is some example code in R
### toy example
N=5
K=6
new.points = expand.grid(1:N,1:N) # grid points
set.seed(1234)
resp=rnorm(N^2) # random values on each grid cell
### function to generate the sequence of candidates
generate<-function(ind){
idx <- seq(1, nrow(new.points), by=1) # index of 1 to N^2 grid cells
swap.points <- c(sample(ind,1),sample(idx[-c(ind)], size=1)) # swap
between points of the initial set and other candidate
ind[which(ind==swap.points[1])]<-idx[which(idx==swap.points[2])]
cat("set =",ind,"\n")
cat("crit =",media(ind),"\n")
cat("swap =",swap.points,"\n")
plot(new.points[,1:2],col='black',xlim=c(range(new.points[,1])),ylim=c(range(new.points[,2])))
points(new.points[ind,1:2],col='blue',pch=19,xlim=c(range(new.points[,1])),ylim=c(range(new.points[,2])))
return(as.numeric(ind))
}
### function to calculate the mean value of the points on the grid
media=function(sq){
med=mean(resp[sq])
return(as.numeric(med))
}
### initial set of K candidates
init=sample(1:K,K)
### run SANN
res <- optim(init, media ,generate, method="SANN",control =
list(maxit=2, temp=100,tmax=1000, trace=TRUE, REPORT=1, fnscale=-1))
new.points[sort(res$par),]
plot(new.points,cex=.1)
points(new.points[res$par,],col=3,lwd=3,cex=1.5)
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[R] Conditional Autoregressive (CAR) model simulation
Hi all ! I would like to simulate spatial lattice/areal data with a conditional autoregressive (CAR) structure, for a given neighbouring matrix and for a autocorrelation "rho". Is there any package or function in R to perform it ? I found the function "CARsimu" in the hdeco library, but this is not what I'm looking for Thanks in advance Dae-Jin -- ______ Dae-Jin Lee Office/Despacho: 7.3.J04 Phone/Tlfno:+34 91 624 9175 Fax: +34 91 624 9430 Departamento de Estadística Av. Universidad 30, Ed. Juan Benet 28911 Leganés (Madrid), SPAIN Universidad Carlos III de Madrid e-mail: [EMAIL PROTECTED] web: http://www.est.uc3m.es/daejin __ [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Conditional Autoregressive (CAR) model simulation
Thanks for your suggestion, Henrique Here I attach a link to some notes by Robert Bivand, with a SAR model, see page 30 www.bias-project.org.uk/ASDARcourse/unit6_slides.pdf The difference with CAR is in the covariance structure, I run and example: # === library(spdep) set.seed(987654) # Columbus example in spdep library example(columbus) n <- length(col.gal.nb) coords <- coordinates(columbus) cards <- card(col.gal.nb) col.w <- nb2listw(col.gal.nb) uncorr_x <- rnorm(n)# uncorrelated random variable cor(uncorr_x, lag(col.w,uncorr_x)) # correlation # == rho <- .5 # spatial autocorrelation # Case1: SAR IrW <- diag(n) - rho*listw2mat(col.w) # I - rho * W SARcov <- solve(t(IrW) %*% IrW) SARcovL <- chol((SARcov + t(SARcov))/2) autocorr_x <- t(SARcovL)%*%uncorr_x cor(autocorr_x, lag(col.w,autocorr_x)) # [,1] [1,] 0.3876456 # == I've did the same but with CAR structure CARcov = solve(IrW) # from (I-rhoW)^ -1 CARcovL = chol(CARcov) # Cholesky Decomposition a_x = t(CARcovL)%*%uncorr_x # cor(a_x,lag(col.W,a_x)) [,1] [1,] 0.06929324 # == I don't know if I'm simulating correctly the CAR, any help? Thanks in advance 2008/2/15, Henrique Dallazuanna <[EMAIL PROTECTED]>: > > See spautolm function in spdep package > > On 15/02/2008, Dae-Jin Lee <[EMAIL PROTECTED]> wrote: > > Hi all ! > > > > I would like to simulate spatial lattice/areal data with a conditional > > autoregressive (CAR) structure, for a given neighbouring matrix and for > a > > autocorrelation "rho". > > > > Is there any package or function in R to perform it ? > > > > I found the function "CARsimu" in the hdeco library, but this is not > what > > I'm looking for > > > > Thanks in advance > > > > Dae-Jin > > > > -- > > __ > > > > Dae-Jin Lee > > > > Office/Despacho: 7.3.J04 > > Phone/Tlfno:+34 91 624 9175 > > Fax: +34 91 624 9430 > > > > Departamento de Estadística > > Av. Universidad 30, Ed. Juan Benet > > 28911 Leganés (Madrid), SPAIN > > Universidad Carlos III de Madrid > > > > e-mail: [EMAIL PROTECTED] > >web: http://www.est.uc3m.es/daejin > > __ > > > > [[alternative HTML version deleted]] > > > > > > __ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > > > > -- > Henrique Dallazuanna > Curitiba-Paraná-Brasil > 25° 25' 40" S 49° 16' 22" O > -- __ Dae-Jin Lee Office/Despacho: 7.3.J04 Phone/Tlfno:+34 91 624 9175 Fax: +34 91 624 9430 Departamento de Estadística Av. Universidad 30, Ed. Juan Benet 28911 Leganés (Madrid), SPAIN Universidad Carlos III de Madrid e-mail: [EMAIL PROTECTED] web: http://www.est.uc3m.es/daejin __ [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] mcv package gamm function Error in chol(XVX + S)
Hi all R users ! I'm using gamm function from Simon Wood's mgcv package, to fit a spatial regression Generalized Additive Mixed Model, as covariates I have the geographical longitude and latitude locations of indexed data. I include a random effect for each district (dist) so the code is fit <- gamm(y~s(lon,lat,bs="tp", m=2)+offset(log(exp.)), random=list(dist=~1), family="poisson", niterPQL=30) when I run the gamm function I obtain the next error message: %%% Maximum number of PQL iterations: 30 iteration 1 iteration 2 ... iteration 8 iteration 9 iteration 10 Error in chol(XVX + S) : the leading minor of order 29 is not positive definite %%% Could be any problem in gamm() ??? -- [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
