Hi,
the predict-function is not very good in guessing names from a given new
dataset. So if you want to predict x1 from some new x2 values, your
newdata argument should contain some x2 - values.
predict(model, newdata=data.frame(x2=seq(0,4)), interval =
c("confidence"), level = 0.90,type="re
It is not an error but rather a warning. As you should have seen, R
went ahead and returned estimates for 24 predicted values for x1 for
arguments to the formula of x2. In R errors and warnings are very
different. You are expected to post full console messages to prevent
this sort of confus
hi,
I don't know what I am doing wrong,
but with that code;
x1 <- c(1.60, 0.27, 0.17, 1.63, 1.37, 2.00, 0.90, 1.07, 0.89, 0.43,
0.37, 0.59,
0.47, 1.83, 1.79, 0.90, 0.72, 1.83, 0.23, 1.97, 2.03, 2.19, 2.03, 0.86)
x2 <- c(1.30, 0.24, 0.20, 0.50, 1.33, 1.87, 1.30, 0.75, 1.07, 0.43,
0.37, 0.8
How about
library(ggplot2)
qplot(wt, mpg, data = mtcars, geom=c("point", "smooth"),method = "lm").
On Sat, Mar 7, 2009 at 6:19 PM, Martin Batholdy wrote:
> hi,
>
>
> is there an easy way to plot the "confidence lines" or "confidence area" of
> the beta weight in a scatterplot?
>
>
> like in this
hi,
is there an easy way to plot the "confidence lines" or "confidence
area" of the beta weight in a scatterplot?
like in this plot;
http://www.ssc.wisc.edu/sscc/pubs/screenshots/4-25/4-25_4.png
thanks!
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