Fortune?
On 1/12/07, Peter Dalgaard <[EMAIL PROTECTED]> wrote:
> Prof Brian Ripley wrote:
> >
> > Where did you tell it 'x' was the abscissa and 'y' the ordinate?
> > (Nowhere: R is lacking a mind_read() function!)
> Please stop complaining about missing features. Patches will be considered.
>
> O
On 1/12/2007 5:56 AM, Barry Rowlingson wrote:
> ken knoblauch wrote:
>> This should do the trick:
>>
>> mind_reader <- function() {
>> ll <- letters[round(runif(6, 1, 26))]
>
> I see my paraNormal distribution package hasn't found its way to CRAN yet:
>
> http://tolstoy.newcastle.edu.au/R/
Barry Rowlingson wrote:
> ken knoblauch wrote:
>> This should do the trick:
>>
>> mind_reader <- function() {
>> ll <- letters[round(runif(6, 1, 26))]
>
> I see my paraNormal distribution package hasn't found its way to CRAN yet:
>
> http://tolstoy.newcastle.edu.au/R/help/05/04/1701.html
ken knoblauch wrote:
> This should do the trick:
>
> mind_reader <- function() {
> ll <- letters[round(runif(6, 1, 26))]
I see my paraNormal distribution package hasn't found its way to CRAN yet:
http://tolstoy.newcastle.edu.au/R/help/05/04/1701.html
Barry
This should do the trick:
mind_reader <- function() {
ll <- letters[round(runif(6, 1, 26))]
ff <- ll[1]
for (ix in 2:length(ll)) {
ff <- paste(ff, ll[ix], sep = "")
}
if (exists(ff)) {
cat("The function that you were t
Prof Brian Ripley wrote:
>
> Where did you tell it 'x' was the abscissa and 'y' the ordinate?
> (Nowhere: R is lacking a mind_read() function!)
Please stop complaining about missing features. Patches will be considered.
Oh, it's you, Brian. Never mind then. You'll get to it, I'm sure.
;-)
--
Tom Backer Johnsen wrote:
> My simpleminded understanding of simple regression is that when
> plotting regression lines for x on y and y on x in the same plot, the
> lines should cross each other at the respective means. But, given the
> R function below, abline (lm(y~x)) works fine, but abli
On Fri, 12 Jan 2007, Tom Backer Johnsen wrote:
> My simpleminded understanding of simple regression is that when
> plotting regression lines for x on y and y on x in the same plot, the
> lines should cross each other at the respective means. But, given the
> R function below, abline (lm(y~x)) wor
On Fri, 12 Jan 2007, Tom Backer Johnsen wrote:
> My simpleminded understanding of simple regression is that when
> plotting regression lines for x on y and y on x in the same plot, the
> lines should cross each other at the respective means. But, given the
> R function below, abline (lm(y~x))
Try this version of your function and then think about it
tst <- function () {
attach (attitude)
x <- rating
y <- learning
detach (attitude)
plot (x, y)
abline(v=mean(x))
abline(h=mean(y))
abline (lm(y~x))
cc <- coef(lm(x ~ y))
abline (-cc[1]/cc[2], 1/cc[2])
}
> My simpleminded understanding of
My simpleminded understanding of simple regression is that when
plotting regression lines for x on y and y on x in the same plot, the
lines should cross each other at the respective means. But, given the
R function below, abline (lm(y~x)) works fine, but abline (lm(x~y))
does not. Why?
funct
Sundar Dorai-Raj writes:
> Hi, Laura,
>
> Would ?predict.glm be better?
>
> plot(logarea, hempresence,
> xlab = "Surface area of log (m2)",
> ylab="Probability of hemlock seedling presence",
> type="n", font.lab=2, cex.lab=1.5, axes=TRUE)
> lines(logarea, predict(hemhem, logreg
Laura M Marx wrote:
> Hi there,
> I've looked through the very helpful advice about adding fitted lines to
> plots in the r-help archive, and can't find a post where someone has offered
> a solution for my specific problem. I need to plot logistic regression fits
> from three differently-si
Hi there,
I've looked through the very helpful advice about adding fitted lines to
plots in the r-help archive, and can't find a post where someone has offered
a solution for my specific problem. I need to plot logistic regression fits
from three differently-sized data subsets on a plot of th
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