Gabor,
I want the new data to be this,
newdata <- data.frame(c(1, 0, 0, 0))
Here the code with the new data,
> dat <- rnorm(20)
> tsdat <- ts(dat, start=c(1900, 1), freq=4)
> q <- as.factor(rep(1:4, 5))
> t <- 1:20
> lm(tsdat~t+q)
Call:
lm(formula = tsdat ~ t + q)
Coefficients:
(Intercept) t q2 q3 q4
-0.167030 -0.009484 0.507132 0.113818 -0.734521
> newdata <- data.frame(c(1, 0, 0, 0))
> predict(model, newdata=newdata)
1 2 3 4 5 6
-0.17651394 0.32113359 -0.08166464 -0.93948758 -0.21445060 0.28319692
7 8 9 10 11 12
-0.11960131 -0.97742425 -0.25238727 0.24526025 -0.15753798 -1.01536092
13 14 15 16 17 18
-0.29032394 0.20732358 -0.19547465 -1.05329759 -0.32826061 0.16938691
19 20
-0.23341132 -1.09123426
Warning message:
'newdata' had 4 rows but variables found have 20 rows
On Sun, Feb 23, 2014 at 6:49 PM, Gabor Grothendieck <ggrothendi...@gmail.com
> wrote:
> On Sun, Feb 23, 2014 at 6:34 PM, C W <tmrs...@gmail.com> wrote:
> > Hello,
> > I don't know how to use predict.lm() for ts object.
> >
> > Here's the time series regression.
> > y = t + Q1 + Q2 + Q3 + Q4
> >
> > Here's my R code,
> >
> >> dat <- rnorm(20)
> >> tsdat <- ts(dat, start=c(1900, 1), freq=4)
> >> q <- as.factor(rep(1:4, 5))
> >> t <- 1:20
> >> lm(tsdat~t+q)
> >
> > Call:
> > lm(formula = tsdat ~ t + q)
> >
> > Coefficients:
> > (Intercept) t q2 q3 q4
> > -0.167030 -0.009484 0.507132 0.113818 -0.734521
> >
> >> predict(model, newdata=newdata)
> > 1 2 3 4 5 6
> > -0.17651394 0.32113359 -0.08166464 -0.93948758 -0.21445060 0.28319692
> > 7 8 9 10 11 12
> > -0.11960131 -0.97742425 -0.25238727 0.24526025 -0.15753798 -1.01536092
> > 13 14 15 16 17 18
> > -0.29032394 0.20732358 -0.19547465 -1.05329759 -0.32826061 0.16938691
> > 19 20
> > -0.23341132 -1.09123426
> > Warning message:
> > 'newdata' had 4 rows but variables found have 20 rows
> >
> >
> > I am aware predict.lm() requires all data to be in data frame format.
> > Could someone tell me what is wrong? Thanks!
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
> Try this:
>
> predict(model)
>
>
> --
> Statistics & Software Consulting
> GKX Group, GKX Associates Inc.
> tel: 1-877-GKX-GROUP
> email: ggrothendieck at gmail.com
>
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