Re: [R] Do YOU know an equation for splines (ns)?
I was able to get the predicted values from the splines. Thanks so much
for the help.
I wrote a loop with some of the code that Bill suggested. It seems that
when using predict with nlme, it is important to be specific with what one
is using as newdata. This does come through in Pinheiro and Bates, I just
didn't recognize it to begin with. Bert, I did try your code, but was only
getting coefficients, so I may have neglected a step.
##The successful code:
library(nlme)
library(splines)
rootCN-read.table(spline.txt, header=3DTRUE)
rootCN$plotF-as.factor(rootCN$plot)
rcn10G-groupedData(N ~ day | plotF, data=3DrootCN)
fit10 - lme( N~ns(day, 3), data =3D rcn10G)
plot(augPred(fit10))
t- 152:305
subject-rootCN[11:22,2]
sim-NULL
for(i in 1:12){
sim- cbind(sim, predict(fit10, data.frame(day=3Dt, plotF=3Drep(subject[i],
length(t)
}
colnames(sim) - c(subject)
par(mfrow=3Dc(4,3))
for(i in 1:12){
plot(t, sim[,i], type=3Dl, main=3Dsubject[i])
}
-Ranae
--
View this message in context:
http://r.789695.n4.nabble.com/Do-YOU-know-an-equation-for-splines-ns-tp4632440p4633037.html
Sent from the R help mailing list archive at Nabble.com.
__
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] Do YOU know an equation for splines (ns)?
I have not been able to get predict (or most functions) to run well with grouped data in nlme. I may not have it coded right, but this is what it looks like: http://r.789695.n4.nabble.com/file/n4632567/spline.txt spline.txt library(nlme) library(splines) rootCN-read.table(spline.txt, header=TRUE) rootCN$plotF-as.factor(rootCN$plot) rcn10G-groupedData(N ~ day | plotF, data=rcn10) fit10 - lme( N~ns(day, 3), data = rcn10G) plot(augPred(fit10)) num- seq(88,300, len=200) lines(num, predict(fit10, data.frame(day=num))) -Ranae Does ?predict.ns not do what you want without having to explicitly manipulate the spline basis? -- Bert On Tue, Jun 5, 2012 at 1:56 PM, Ranae [hidden email] wrote: Hi, I am looking at the change in N concentration in plant roots over 4 time points and I have fit a spline to the data using ns and lme: fit10 - lme( N~ns(day, 3), data = rcn10G) I may want to adjust the model a little bit, but for now, let's assume it's good. I get output for the fixed effects: Fixed: N ~ ns(day, 3) (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 1.15676524 0.14509171 0.04459627 0.09334428 and coefficients for each experimental unit in my experiment: (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 241.050360 -0.42666159 -0.56290877 -0.10714407 131.104464 -0.30825350 -0.53311653 -0.05558150 311.147878 -0.14548512 -0.78673906 -0.07231781 461.177781 -0.22278380 -0.80278177 -0.02321460 151.144215 -0.04484519 -0.06084798 0.07633663 321.213007 0.00741061 0.03896933 0.15325849 231.274615 0.16477514 0.00872224 0.23128320 411.215626 0.57050767 0.11415467 0.10608867 431.134203 0.48070741 0.72112899 0.18108193 121.091422 0.39563632 1.01521528 0.22597459 211.100631 0.44589314 0.98526322 0.23535739 351.226980 0.82419937 0.39809568 0.16900841 NOW, I want to write a spline function where I can incorporate these coefficients to get the predicted N concentration value for each day. However, I am having trouble finding the right spline equation, since there are many forms on the internets. I know it won't be a simple one, but can some one direct me to the equation that would be best to use for ns? Thanks a lot, Ranae -- View this message in context: http://r.789695.n4.nabble.com/Do-YOU-know-an-equation-for-splines-ns-tp4632440p4632567.html Sent from the R help mailing list archive at Nabble.com. __ 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] Do YOU know an equation for splines (ns)?
Ah ... Iirc believe the problem is that you need to explicitly generate the spline basis and then the predicted values via predict.ns and feed that to predict.lme; i.e. splineBas - with(rcn10,ns(day,3)) newvals - data.frame( predict(splineBas, num)) ## then once you've fitted your model: lines(num, predict(fit10, newvals)) I have NOT checked this though, so please post back to me and the list whether this works. -- Bert On Wed, Jun 6, 2012 at 10:38 AM, Ranae ranae.diet...@gmail.com wrote: I have not been able to get predict (or most functions) to run well with grouped data in nlme. I may not have it coded right, but this is what it looks like: http://r.789695.n4.nabble.com/file/n4632567/spline.txt spline.txt library(nlme) library(splines) rootCN-read.table(spline.txt, header=TRUE) rootCN$plotF-as.factor(rootCN$plot) rcn10G-groupedData(N ~ day | plotF, data=rcn10) fit10 - lme( N~ns(day, 3), data = rcn10G) plot(augPred(fit10)) num- seq(88,300, len=200) lines(num, predict(fit10, data.frame(day=num))) -Ranae Does ?predict.ns not do what you want without having to explicitly manipulate the spline basis? -- Bert On Tue, Jun 5, 2012 at 1:56 PM, Ranae [hidden email] wrote: Hi, I am looking at the change in N concentration in plant roots over 4 time points and I have fit a spline to the data using ns and lme: fit10 - lme( N~ns(day, 3), data = rcn10G) I may want to adjust the model a little bit, but for now, let's assume it's good. I get output for the fixed effects: Fixed: N ~ ns(day, 3) (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 1.15676524 0.14509171 0.04459627 0.09334428 and coefficients for each experimental unit in my experiment: (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 24 1.050360 -0.42666159 -0.56290877 -0.10714407 13 1.104464 -0.30825350 -0.53311653 -0.05558150 31 1.147878 -0.14548512 -0.78673906 -0.07231781 46 1.177781 -0.22278380 -0.80278177 -0.02321460 15 1.144215 -0.04484519 -0.06084798 0.07633663 32 1.213007 0.00741061 0.03896933 0.15325849 23 1.274615 0.16477514 0.00872224 0.23128320 41 1.215626 0.57050767 0.11415467 0.10608867 43 1.134203 0.48070741 0.72112899 0.18108193 12 1.091422 0.39563632 1.01521528 0.22597459 21 1.100631 0.44589314 0.98526322 0.23535739 35 1.226980 0.82419937 0.39809568 0.16900841 NOW, I want to write a spline function where I can incorporate these coefficients to get the predicted N concentration value for each day. However, I am having trouble finding the right spline equation, since there are many forms on the internets. I know it won't be a simple one, but can some one direct me to the equation that would be best to use for ns? Thanks a lot, Ranae -- View this message in context: http://r.789695.n4.nabble.com/Do-YOU-know-an-equation-for-splines-ns-tp4632440p4632567.html Sent from the R help mailing list archive at Nabble.com. __ 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ 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] Do YOU know an equation for splines (ns)?
Do you have to include the grouping variable, plotF, in your newdata argument? E.g., after fitting the model with rcn10G-groupedData(N ~ day | plotF, data=rcn10) fit10 - lme( N~ns(day, 3), data = rcn10G) try checking the predictions when you've include plotF in newdata: par(mfrow=c(2,1)) plot(N ~ day, subset=plotF==12, data=rcn10G) points(num, predict(fit10, data.frame(day=num, plotF=rep(12, length(num, pch=., col=red) plot(N ~ day, subset=plotF==43, data=rcn10G) points(num, predict(fit10, data.frame(day=num, plotF=rep(43, length(num, pch=., col=red) I am no expert on the lme and groupedData, but the general rule is that all variables involved in the model, except the response, must be given to predict. Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Ranae Sent: Wednesday, June 06, 2012 10:39 AM To: r-help@r-project.org Subject: Re: [R] Do YOU know an equation for splines (ns)? I have not been able to get predict (or most functions) to run well with grouped data in nlme. I may not have it coded right, but this is what it looks like: http://r.789695.n4.nabble.com/file/n4632567/spline.txt spline.txt library(nlme) library(splines) rootCN-read.table(spline.txt, header=TRUE) rootCN$plotF-as.factor(rootCN$plot) rcn10G-groupedData(N ~ day | plotF, data=rcn10) fit10 - lme( N~ns(day, 3), data = rcn10G) plot(augPred(fit10)) num- seq(88,300, len=200) lines(num, predict(fit10, data.frame(day=num))) -Ranae Does ?predict.ns not do what you want without having to explicitly manipulate the spline basis? -- Bert On Tue, Jun 5, 2012 at 1:56 PM, Ranae [hidden email] wrote: Hi, I am looking at the change in N concentration in plant roots over 4 time points and I have fit a spline to the data using ns and lme: fit10 - lme( N~ns(day, 3), data = rcn10G) I may want to adjust the model a little bit, but for now, let's assume it's good. I get output for the fixed effects: Fixed: N ~ ns(day, 3) (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 1.15676524 0.14509171 0.04459627 0.09334428 and coefficients for each experimental unit in my experiment: (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 241.050360 -0.42666159 -0.56290877 -0.10714407 131.104464 -0.30825350 -0.53311653 -0.05558150 311.147878 -0.14548512 -0.78673906 -0.07231781 461.177781 -0.22278380 -0.80278177 -0.02321460 151.144215 -0.04484519 -0.06084798 0.07633663 321.213007 0.00741061 0.03896933 0.15325849 231.274615 0.16477514 0.00872224 0.23128320 411.215626 0.57050767 0.11415467 0.10608867 431.134203 0.48070741 0.72112899 0.18108193 121.091422 0.39563632 1.01521528 0.22597459 211.100631 0.44589314 0.98526322 0.23535739 351.226980 0.82419937 0.39809568 0.16900841 NOW, I want to write a spline function where I can incorporate these coefficients to get the predicted N concentration value for each day. However, I am having trouble finding the right spline equation, since there are many forms on the internets. I know it won't be a simple one, but can some one direct me to the equation that would be best to use for ns? Thanks a lot, Ranae -- View this message in context: http://r.789695.n4.nabble.com/Do-YOU-know-an- equation-for-splines-ns-tp4632440p4632567.html Sent from the R help mailing list archive at Nabble.com. __ 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-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] Do YOU know an equation for splines (ns)?
I agree with Bill and Bert: predict is the proper tool for
making predictions. Pinheiro and Bates (2000) Mixed-Effects Models in S
and S-Plus (Springer) includes several entries in the index for
predictions. Please note, however, that there are a few lines of code
in that book the work in S-Plus but not R. Fortunately, the corrections
are available in script files distributed with the package, which you
can find as follows:
system.file('scripts', package='nlme')
[1] c:/Program Files/R/R-2.15.0/library/nlme/scripts
The TaylorSpline{fda} function will give you explicit
coefficients each segment of a spline. However, if you want model
predictions, you are probably best using predict with objects produced
by functions in nlme. That package has seen lots of use and attention
by the R Core team, and should be pretty good -- especially with the
documentation provided by Pinheiro and Bates.
Hope this helps.
Spencer
On 6/6/2012 1:48 PM, William Dunlap wrote:
Do you have to include the grouping variable, plotF, in your newdata
argument? E.g., after fitting the model with
rcn10G-groupedData(N ~ day | plotF, data=rcn10)
fit10- lme( N~ns(day, 3), data = rcn10G)
try checking the predictions when you've include plotF in newdata:
par(mfrow=c(2,1))
plot(N ~ day, subset=plotF==12, data=rcn10G)
points(num, predict(fit10, data.frame(day=num, plotF=rep(12, length(num,
pch=., col=red)
plot(N ~ day, subset=plotF==43, data=rcn10G)
points(num, predict(fit10, data.frame(day=num, plotF=rep(43, length(num,
pch=., col=red)
I am no expert on the lme and groupedData, but the general rule is that all
variables involved
in the model, except the response, must be given to predict.
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf
Of Ranae
Sent: Wednesday, June 06, 2012 10:39 AM
To: r-help@r-project.org
Subject: Re: [R] Do YOU know an equation for splines (ns)?
I have not been able to get predict (or most functions) to run well with
grouped data in nlme. I may not have it coded right, but this is what it
looks like:
http://r.789695.n4.nabble.com/file/n4632567/spline.txt spline.txt
library(nlme)
library(splines)
rootCN-read.table(spline.txt, header=TRUE)
rootCN$plotF-as.factor(rootCN$plot)
rcn10G-groupedData(N ~ day | plotF, data=rcn10)
fit10- lme( N~ns(day, 3), data = rcn10G)
plot(augPred(fit10))
num- seq(88,300, len=200)
lines(num, predict(fit10, data.frame(day=num)))
-Ranae
Does
?predict.ns
not do what you want without having to explicitly manipulate the spline
basis?
-- Bert
On Tue, Jun 5, 2012 at 1:56 PM, Ranae[hidden email] wrote:
Hi,
I am looking at the change in N concentration in plant roots over 4 time
points and I have fit a spline to the data using ns and lme:
fit10- lme( N~ns(day, 3), data = rcn10G)
I may want to adjust the model a little bit, but for now, let's assume
it's
good. I get output for the fixed effects:
Fixed: N ~ ns(day, 3)
(Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3
1.15676524 0.14509171 0.04459627 0.09334428
and coefficients for each experimental unit in my experiment:
(Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3
241.050360 -0.42666159 -0.56290877 -0.10714407
131.104464 -0.30825350 -0.53311653 -0.05558150
311.147878 -0.14548512 -0.78673906 -0.07231781
461.177781 -0.22278380 -0.80278177 -0.02321460
151.144215 -0.04484519 -0.06084798 0.07633663
321.213007 0.00741061 0.03896933 0.15325849
231.274615 0.16477514 0.00872224 0.23128320
411.215626 0.57050767 0.11415467 0.10608867
431.134203 0.48070741 0.72112899 0.18108193
121.091422 0.39563632 1.01521528 0.22597459
211.100631 0.44589314 0.98526322 0.23535739
351.226980 0.82419937 0.39809568 0.16900841
NOW, I want to write a spline function where I can incorporate these
coefficients to get the predicted N concentration value for each day.
However, I am having trouble finding the right spline equation, since
there
are many forms on the internets.
I know it won't be a simple one, but can some one direct me to the
equation
that would be best to use for ns?
Thanks a lot,
Ranae
--
View this message in context: http://r.789695.n4.nabble.com/Do-YOU-know-an-
equation-for-splines-ns-tp4632440p4632567.html
Sent from the R help mailing list archive at Nabble.com.
__
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-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
[R] Do YOU know an equation for splines (ns)?
Hi, I am looking at the change in N concentration in plant roots over 4 time points and I have fit a spline to the data using ns and lme: fit10 - lme( N~ns(day, 3), data = rcn10G) I may want to adjust the model a little bit, but for now, let's assume it's good. I get output for the fixed effects: Fixed: N ~ ns(day, 3) (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 1.15676524 0.14509171 0.04459627 0.09334428 and coefficients for each experimental unit in my experiment: (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 241.050360 -0.42666159 -0.56290877 -0.10714407 131.104464 -0.30825350 -0.53311653 -0.05558150 311.147878 -0.14548512 -0.78673906 -0.07231781 461.177781 -0.22278380 -0.80278177 -0.02321460 151.144215 -0.04484519 -0.06084798 0.07633663 321.213007 0.00741061 0.03896933 0.15325849 231.274615 0.16477514 0.00872224 0.23128320 411.215626 0.57050767 0.11415467 0.10608867 431.134203 0.48070741 0.72112899 0.18108193 121.091422 0.39563632 1.01521528 0.22597459 211.100631 0.44589314 0.98526322 0.23535739 351.226980 0.82419937 0.39809568 0.16900841 NOW, I want to write a spline function where I can incorporate these coefficients to get the predicted N concentration value for each day. However, I am having trouble finding the right spline equation, since there are many forms on the internets. I know it won't be a simple one, but can some one direct me to the equation that would be best to use for ns? Thanks a lot, Ranae -- View this message in context: http://r.789695.n4.nabble.com/Do-YOU-know-an-equation-for-splines-ns-tp4632440.html Sent from the R help mailing list archive at Nabble.com. __ 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] Do YOU know an equation for splines (ns)?
Does ?predict.ns not do what you want without having to explicitly manipulate the spline basis? -- Bert On Tue, Jun 5, 2012 at 1:56 PM, Ranae ranae.diet...@gmail.com wrote: Hi, I am looking at the change in N concentration in plant roots over 4 time points and I have fit a spline to the data using ns and lme: fit10 - lme( N~ns(day, 3), data = rcn10G) I may want to adjust the model a little bit, but for now, let's assume it's good. I get output for the fixed effects: Fixed: N ~ ns(day, 3) (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 1.15676524 0.14509171 0.04459627 0.09334428 and coefficients for each experimental unit in my experiment: (Intercept) ns(day, 3)1 ns(day, 3)2 ns(day, 3)3 24 1.050360 -0.42666159 -0.56290877 -0.10714407 13 1.104464 -0.30825350 -0.53311653 -0.05558150 31 1.147878 -0.14548512 -0.78673906 -0.07231781 46 1.177781 -0.22278380 -0.80278177 -0.02321460 15 1.144215 -0.04484519 -0.06084798 0.07633663 32 1.213007 0.00741061 0.03896933 0.15325849 23 1.274615 0.16477514 0.00872224 0.23128320 41 1.215626 0.57050767 0.11415467 0.10608867 43 1.134203 0.48070741 0.72112899 0.18108193 12 1.091422 0.39563632 1.01521528 0.22597459 21 1.100631 0.44589314 0.98526322 0.23535739 35 1.226980 0.82419937 0.39809568 0.16900841 NOW, I want to write a spline function where I can incorporate these coefficients to get the predicted N concentration value for each day. However, I am having trouble finding the right spline equation, since there are many forms on the internets. I know it won't be a simple one, but can some one direct me to the equation that would be best to use for ns? Thanks a lot, Ranae -- View this message in context: http://r.789695.n4.nabble.com/Do-YOU-know-an-equation-for-splines-ns-tp4632440.html Sent from the R help mailing list archive at Nabble.com. __ 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ 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.
