shorter way of coding

________________________________________
Fr?n: Sarah Goslee [sarah.goslee at gmail.com]
Skickat: den 12 december 2011 17:36
Till: Mintewab Bezabih
Kopia: r-help at r-project.org
?mne: Re: [R] shorter way of coding

That's not a reproducible example. Paul suggested a list of formulas,
but I recommended creating a list of y variables.

In your attempt, you didn't include the y in the name of the dependent
variable; that's probably why it doesn't work.

Look at this:

y.list <- list(y1=runif(10), y2 <- runif(10), y3 <- runif(10))
x1 <- 1:10
lapply(y.list, function(y)lm(y ~ x1))
$y1

Call:
lm(formula = y ~ x1)

Coefficients:
(Intercept)           x1
   0.56392     -0.02586


[[2]]

Call:
lm(formula = y ~ x1)

Coefficients:
(Intercept)           x1
   0.66375     -0.03519


[[3]]

Call:
lm(formula = y ~ x1)

Coefficients:
(Intercept)           x1
   0.29106      0.02845

Sarah

On Mon, Dec 12, 2011 at 11:21 AM, Mintewab Bezabih
<Mintewab.Bezabih at economics.gu.se> wrote:
Dear Paul and Sarah

Thanks for the suggestion. I have provided my data here in to make the results reproducable. I am actually trying to do interpoliation of climate data where x1 and x2 are my latitude and longitude and sum64-sum 368 are my rainfall observations which I need to regress against x1 and x2. In the previous I was trying to get my story clear so I did not go into details.

Now when I run your suggestion below, I get the following error message. Is there anything in your instruction that I did not get right?
many thanks
mintewab

listOfForumlas = paste(1:300, "~s(x1,x2, k=100)")
listofResults = lapply(listOfForumlas, function(f) {
   b<-gam(as.formula(f),data=dat)
   vis.gam(b)
   fitted(b)
 })

Error in model.frame.default(formula = 1 ~ 1 + x1+ x2, data = dat,  :
 variable lengths differ (found for 'x1')
________________________________________
Fr?n: Paul Hiemstra [paul.hiemstra at knmi.nl]
Skickat: den 12 december 2011 14:42
Till: Mintewab Bezabih
Kopia: r-help at r-project.org
?mne: Re: [R] shorter way of coding

On 12/12/2011 01:16 PM, Mintewab Bezabih wrote:
Dear R users,

I am using the code below to generate a fitted value of b. I have about 300 different values for for y (y1, y2, ...y300) which means I will have to write the code below 300 times to generate the 300 different fitted values for y. Is there a short way of doing that ?

Many thanks in advance
Mintewab

library(mgcv)
dat <- read.table("e:/minti's laptop/C/GBG/allround_survey/rainfallGPS.csv", header=T, sep=",")
b<-gam(y1~s(x1, x2, k=100),data=dat)
vis.gam(b)
fitted(b)
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and provide commented, minimal, self-contained, reproducible code.

Hi Mintewab,

Something along these lines should work:

listOfForumlas = paste(1:300, "~s(x1, x2, k=100)")
listofResults = lapply(listOfForumlas, function(f) {
   b<-gam(as.formula(f),data=dat)
   vis.gam(b)
   fitted(b)
 })

But as Sarah already commented, without a reproducible piece of example
code we cannot present any working solutions.

cheers,
Paul