# [R] Res: predict from a multiple regression model

From: Milton Cezar Ribeiro <milton_ruser_at_yahoo.com.br>
Date: Tue, 22 Jan 2008 09:28:46 -0800 (PST)

Hi Franzi,

Up to I know you can´t predict values without you have x2,x3 and x4 parameters. So you have three possible solution

1. set x2, x3 and x4 to Zero, *but* it will depend so much of what you want, because if you set them to zero, it means that you are adjusting something like mod<-lm(y~x1)
2. set x2,x3 and x4 to and mean value that you understand as rasonable for your purpose] and
3. build a set of for () looping, with the ranges of x2, x3 and x4, and see what happens with the y, for each combination of x1-x2-x3-x4.

y<-runif(101)

```x1<-sample(seq(0, 100))
x2<-seq(from=0,to=100,by=1)
x3<-seq(from=0,to=100,by=1)^2
x4<-exp(seq(from=0,to=100,by=1))
df<-data.frame(cbind(y,x1,x2,x3,x4))
```

mod<-lm(y~x1+x2+x3+x3,data=df)

df.complete<-NULL

```for (x2 in seq(from=0,to=100,by=20)) {
for (x3 in seq(from=0,to=100,by=20)) {
for (x4 in seq(from=0,to=100,by=20)) {
```

x1<-seq(0, 100, by=10)

```    df.new<-data.frame(cbind(x1,x2,x3,x4))
df.new\$pred<-predict(mod,new=df.new)
df.complete<-rbind(df.complete,df.new)
```
}}}

summary(df.complete)

But you have a problema. If you have four dimensions (x1-x4), it is so hard to graph. In the case of two dimensions (like x1 and x2) you can use the function interp() function of akima´s packge to generate a 3d plot of your response variavel y-pred as a surface.

Good luck,

miltinho
Brazil

• Mensagem original ---- De: Fränzi Korner <fraenzi.korner_at_oikostat.ch> Para: r-help_at_r-project.org Enviadas: Terça-feira, 22 de Janeiro de 2008 11:50:03 Assunto: [R] predict from a multiple regression model

Hello

how can I predict from a lm-object over a range of values of one explanatory variable without having to specify values for all the other explanatory variables?

e.g.

mod<-lm(y~x1+x2+x3+x4)

x1.new<-seq(0, 100)

predict(mod, new=list(x1=x1.new))

Here, predict() does not work, since values for x2, x3 and x4 are missing. Is there a function or argument that, in such a case, averages or weights over the other explanatory variables, how it is done in Genstat?

Thanks

Fränzi

Dr. Fränzi Korner-Nievergelt

oikostat - Statistische Analysen und Beratung

Ausserdorf 43

CH - 6218 Ettiswil

Tel.: +41 (0) 41 980 49 22

www.oikostat.ch

Schweizerische Vogelwarte

CH - 6204 Sempach

www.vogelwarte.ch

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