Spencer Graves <[EMAIL PROTECTED]> writes:
> Bates and Watts (1988) Nonlinear Regression Analysis and Its
> Applications (Wiley) explain that parameter effects curvature
> seems to be vastly greater than the "intrinsic curvature" of the
> nonlinear manifold, onto which a res
Loops are time consuming in R. Try one of the apply functions for vectorized
calculations, like "apply", "lapply","sapply" or "tapply". Also see help for
"split".
In a message dated 10/19/03 5:25:51 PM Pacific Daylight Time,
[EMAIL PROTECTED] writes:
> Hello All,
> I am new to R. I am tr
If the algorithm works properly, you should get exactly the same
answer using a linear or a log scale for the parameters.
The bigger question is not bias but the accuracy of a normal
approximation for confidence intervals and regions. I have evaluated
this by making contour plots of
Manoj - Hachibushu Capital wrote:
I am new to R. I am trying to process this huge data set of
matrix containing four columns, say x1, x2, x3, x4 and n number of rows.
I want to aggregate the matrix by x1 and perform statistic based on
columns x2, x3, x4.
Someone will probably give you a
Spencer Graves <[EMAIL PROTECTED]> writes:
> I have not used "nlm", but that happens routinely with function
> minimizers trying to test negative values for one or more
> component of x. My standard approach to something like this is
> to parameterize "llfunc" in terms of l
Hello All,
I am new to R. I am trying to process this huge data set of
matrix containing four columns, say x1, x2, x3, x4 and n number of rows.
I want to aggregate the matrix by x1 and perform statistic based on
columns x2, x3, x4. I tried aggregate function but it gave me memory
all
I have not used "nlm", but that happens routinely with function
minimizers trying to test negative values for one or more component of
x. My standard approach to something like this is to parameterize
"llfunc" in terms of log(shape) and log(scale), as follows:
llfunc <- function (x) { -s
I'm trying to fit a Weibull distribution to some data via maximum
likelihood estimation. I'm following the procedure described by Doug
Bates in his "Using Open Source Software to Teach Mathematical
Statistics" but I keep getting warnings about NaNs being converted to
maximum positive value:
> llfu
On Sunday 19 October 2003 16:31, Martin Wegmann wrote:
> Hello,
>
> I tried to open lattice, but I get the following error:
> > library(lattice)
>
> Error in loadNamespace(i, c(lib.loc, .libPaths()), keep.source) :
> package `grid' does not have a name space
> Error in library(lattice) : pa
Hi
Deepayan Sarkar wrote:
On Friday 17 October 2003 02:20, Martin Maechler wrote:
"PaulSch" == Schwarz, Paul <[EMAIL PROTECTED]>
on Wed, 15 Oct 2003 12:09:11 -0700 writes:
PaulSch> I am converting some S-PLUS scripts that I use for
PaulSch> creating manuscript figures to R so that I can
Since there doesn't appear to be an RMySQL rpm for SuSE 8.*, does
anyone know if the 7.3 version will work with the SuSE 8.2 rpms of R and
DBI?
The package installs without complaint, but when I try to run
con <- dbConnect(dbDriver("MySQL"),dbname="test")
I get the error
Error in dbCon
I started to notice this when I moved to 1.8.0 and e.g. load MASS.
Rob
On Sunday, October 19, 2003, at 02:31 PM, Martin Wegmann wrote:
Hello,
I tried to open lattice, but I get the following error:
library(lattice)
Error in loadNamespace(i, c(lib.loc, .libPaths()), keep.source) :
packa
Hello,
I tried to open lattice, but I get the following error:
> library(lattice)
Error in loadNamespace(i, c(lib.loc, .libPaths()), keep.source) :
package `grid' does not have a name space
Error in library(lattice) : package/namespace load failed
>
I retyped it after loading grid but t
System info:
Red Hat 9.0
R Version 1.8.0
ESS 5.1.21
Emacs 21.2.1
---
Hello
I've been working with Paul Murrell here in New Zealand to develop plots
of temperature and density profiles at 22 stations spanning a frontal
zxone, and then overlaying the isothermal and mixed layer dept
Hi
[EMAIL PROTECTED] wrote:
As an absolute beginner I'm reading and practicing with the Verzani doc to learn R.
Now, being an expert latex user who wants to integrate graphical capabilities if R and latex,
using the "Simple" library and the simple.scatterplot examples I had a go at:
1) Includi
On Sunday 19 October 2003 11:49, Paul, David A wrote:
> For the first error message:
> > win.metafile(file = "//.../plot1.wmf",
> + width = 8.5, height = 6.25)
Could you check what the value of the .Device variable (and .Devices as well)
is at this point ? And not that it should matter, but what
For the first error message:
> win.metafile(file = "//.../plot1.wmf",
+ width = 8.5, height = 6.25)
> lset( list( background = list(col = "white")))
Error in get(x, envir, mode, inherits) :
variable "win.metafile://.../plot1.wmf" was not found
> traceback()
4: get(device)
3: trellis.device(devi
R1.8.0, Win2k:
When I paste the code
win.metafile(file = "//.../plot1.wmf",
width = 8.5, height = 6.25)
lset( list( background = list(col = "white")))
xyplot( y ~ x | ID, data = Group1,
scales = list(alternating = FALSE),
ylim = c(.75,y.max),
panel = function(x,
On 19 Oct 2003 at 11:02, Paul Meagher wrote:
You could look at chapter 5 of Jim Lindset's online document
"The statistical analysis of stochastic processes in Time", at his
website, www.luc.ac.be/~jlindsey
At this site there is also a collection of R functions for his
examples.
Kjetil Halvorsen
I just got several hits from "www.r-project.org" -> search -> "R site
search" for "Markov chain", "Markov chain estimation", etc. Have you
tried that?
help this helps. spencer graves
Paul Meagher wrote:
Can someone give me a pointer to where I should be looking for markov chain
resources in
Can someone give me a pointer to where I should be looking for markov chain
resources in R?
Longer term, I am also interested in the question of whether explanatory
variables can coupled to a probability transition matrix to assist in
predicting the next state that a an object/system will go into.
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