Do YOU know an equation for splines (ns)?

system.file('scripts', package='nlme')

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-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf
Of Ranae
Sent: Wednesday, June 06, 2012 10:39 AM
To: r-help at 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
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

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