shorter way of coding
In exactly the same way: y.gam <- lapply(y.list, function(y)gam(y~s(x1,x2, k=1))) # list of gam objects y.vis.gam <- lapply(y.gam, vis.gam) # list of vis.gam outputs y.fitted <- lapply(y.gam, fitted) # list of fitted values. Saraj On Tue, Dec 13, 2011 at 10:48 AM, Mintewab Bezabih
<Mintewab.Bezabih at economics.gu.se> wrote:
Dear Sarah and R users, Thanks Sarah for the suggestion. The example you gave me works and I managed to get it to run by modifying the 'lm' to the gam command. y.list <- list(y1=runif(10), y2 <- runif(10), y3 <- runif(10)) x1 <- 1:10 x2 <- c(11, 15, 17, 2, 18, 6, 7, 8, 12, 10) lapply(y.list, function(y)gam(y~s(x1,x2, k=100))) I now face problem of getting the fitted results from the gam command. My original problem for only one y looked like this. Now how do I get to incorporate vis.gam(b) and fitted (b) into my new code? b<-gam(y~s(x1,x2,k=100),data=dat) vis.gam(b) fitted(b) Many thanks once again. Mintewab
________________________________________
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
Sarah Goslee http://www.functionaldiversity.org