On 5/6/21 6:29 PM, Jim Lemon wrote:
Hi James,
If the result contains the major (a) and minor (b) axes of the
ellipse, it's easy:
area<-pi*a*b
ITYM semi-major and semi-minor axes.
--
David
try using str() on the result you get.
Jim
On Fri, May 7, 2021 at 3:51 AM james meyer wrote:
lm (cl$y ~ cl$x)$coef
(Intercept)cl$x
0.1817509 -1.000
On Fri, May 7, 2021 at 1:56 PM Abbs Spurdle wrote:
>
> #using vF1 function
> #from my previous posts
> u <- seq (0, 0.25,, 200)
> cl <- contourLines (u, u, outer (u, u, vF1),, 0)[[1]]
> plot (cl$x, cl$y, type="l")
>
>
> On Thu
#using vF1 function
#from my previous posts
u <- seq (0, 0.25,, 200)
cl <- contourLines (u, u, outer (u, u, vF1),, 0)[[1]]
plot (cl$x, cl$y, type="l")
On Thu, May 6, 2021 at 10:18 PM Ursula Trigos-Raczkowski
wrote:
>
> Thanks for your reply. Unfortunately the code doesn't work even when I change
Hi James,
If the result contains the major (a) and minor (b) axes of the
ellipse, it's easy:
area<-pi*a*b
try using str() on the result you get.
Jim
On Fri, May 7, 2021 at 3:51 AM james meyer wrote:
>
> In doing meta-analysis of diagnostic accuracy I produce ellipses of confidence
> and predic
This looks like homework. We don't do homework on this list.
To see what is done here, read and follow the posting guide linked below.
If not homework, I think it is still very much out of bounds anyway, as
you appear to be asking us to do your work for you.
On Thu, May 6, 2021, 2:32 PM Ahmad Ra
Dear Experts,
Greetings
I have the following type of repeated measures data (table 1), and events
data in table 2 (single measure). I want to perform the following tasks (in
R or excel sheet please).
- To filter subjects who had any response at least 3 days.
- Response should be > 5 in each
Posting HTML email is a good way to reduce your chances of getting a response.
On May 6, 2021 1:13:16 PM PDT, Jeff Reichman wrote:
>R-help
>
>Never mind I figured out a working solution
>
>- remove duplicate
>- mutate a new column == 1
>- spread the data from long to wide
>- replace NA with 0's
R-help
Never mind I figured out a working solution
- remove duplicate
- mutate a new column == 1
- spread the data from long to wide
- replace NA with 0's
Not sure it’s the most elegant but gets the gob done
-Original Message-
From: R-help On Behalf Of Jeff Reichman
Sent: Thursday,
R Help Forum
I am attempting to transform the data frame in Table 1 to the form shown in
Table 2. Any suggestions. I�ve started by removing duplicate rows
Jeff
Table 1
Taxon
Importer
Guarouba guarouba
AE
Acipenser gueldenstaedtii
AE
Caiman crocodilus fuscus
AE
Caiman croc
Dear James,
To mix notation a bit, presumably the (border of the) confidence ellipse
is of the form (b - beta)'V(b)^-1 (b - beta) = c, where V(b) is the
covariance matrix of b and c is a constant. Then the area of the ellipse
is pi*c^2*sqrt(det(V(b))). It shouldn't be hard to translate that in
In doing meta-analysis of diagnostic accuracy I produce ellipses of confidence
and prediction intervals in two dimensions. How can I calculate the area of
the ellipse in ggplot2 or base R?
thank you
James Meyer
__
R-help@r-project.org mailing list -- T
Thanks for your reply. Unfortunately the code doesn't work even when I
change the parameters to ensure I have "different" equations.
Using mathematica I do see that my two equations form planes, intersecting
in a line of infinite solutions but it is not very accurate, I was hoping R
would be more a
Just realized five minutes after posting that I misinterpreted your
question, slightly.
However, after comparing the solution sets for *both* equations, I
can't see any obvious difference between the two.
If there is any difference, presumably that difference is extremely small.
On Thu, May 6, 20
Hi Ursula,
If I'm not mistaken, there's an infinite number of solutions, which
form a straight (or near straight) line.
Refer to the following code, and attached plot.
begin code---
library (barsurf)
vF1 <- function (u, v)
{ n <- length (u)
k <- numeric (n)
for (i in seq_len (n) )
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