Faheem Mitha wrote:
Monotonic Multigamma run ( * n == len * , * theta == t1 *
Is this a valid expression? My understanding of an expression is that it
contains one more more statements.
That's only part of the expression. This is the full expression
Monotonic Multigamma run ( * n == len * ,
Hi Folks,
Could anyone point me to a good reference on linear regression models? Specifically,
I am trying to gain an intuitive feel for how the standard error values are calculated
for the parameter estimates. My understanding is that these are computed using the
variance-covariance
Dear James,
A very nice way of understanding these matters intuitively is to express
them geometrically using data and confidence ellipses (for two predictors
and their coefficients) and ellipsoids (more generally). The same ideas
apply to linear hypotheses, such as for the difference between
Yes, statisticians call the natural versions of the cumulative normal
distribution, pnorm. As I recall
erf(x) = 2 * pnorm(x * sqrt(2)) - 1
erfc(x) = 2 * pnorm(x * sqrt(2), lower=FALSE)
On Sat, 21 Jun 2003, Salvatore Barbaro wrote:
does anybody know if R contains error functions like
erf
BDR == Prof Brian Ripley [EMAIL PROTECTED]
on Sat, 21 Jun 2003 06:44:00 +0100 (BST) writes:
BDR ?try is your friend here.
Yes, but Jonck's real problem is the use of an outdated version
of the cluster package (yes: package, *not* library).
Which proves that he is certainly *not*
There seems to exist peculiar cases where optim does not take care
of constraints on the parameters to be optimized over. The call to
optim is of the form
opt - optim(cp, fn=sn.dev, gr=sn.dev.gh, method=L-BFGS-B,
lower=c(-Inf, 1e-10, -0.99527),
upper=c( Inf, Inf,
Adelchi:
Permit me to add to Prof. Ripley's comments:
If you want to know how to get around this kind of problem, I will
tell you that I would modify the definition of cp to send the
constraints to +/-Inf. Functions like optim tend to work better with
unconstrained problems than
John Fox was kind enough to reply, but didn't recommend IMHO the best book
on regression models: his own, John Fox, _An R and S-Plus Companion to
Applied Regression_, Sage, 2002.
ap
--
Andrew J Perrin -
On Sat, 21 Jun 2003, Uwe Ligges wrote:
Faheem Mitha wrote:
Can you go into a little more detail here about why alpha here is a
call?
Thomas already told it and ?expression says as well: expression returns
a vector of mode expression containing its arguments as unevaluated
``calls''.
Dear R users, I have a question on using weighted.mean() while aggregating a
data frame. I have a data frame with columns Sub, Length and Slope:
x[1:5,]
Sub LengthSlope
1 2 351.547 0.0025284969
2 2 343.738 0.0025859390
3 1 696.659 0.0015948968
4 2 5442.338 0.0026132544
5
tstdf - data.frame(Sub =rep(1:2, 2),
+ Length=1:4, Slope=11:14)
by(tstdf, tstdf$Sub,
+ function(x)weighted.mean(x$Slope, x$Length))
tstdf$Sub: 1
[1] 12.5
tstdf$Sub: 2
[1] 13.3
Does this answer your question?
hth. spencer graves
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