On 30/12/2013 22:57, Simon Zehnder wrote:
Why not using optim on the likelihood in a) with normally distributed standard
errors and for b) optim with a likelihood with t(3)-distributed standard errors?
Because evaluating the likelihood is a tricky business here.
I don't know what is meant by
A.K. answered your question 1, but since you did say as question 2 that you
wanted it done right...
library(reshape2)
ex3 <- function() {
d <- data.frame(x=1:5,a=1:5,b=2:6,c=3:7)
dl <- melt( d, id.vars="x" )
ggplot(dl,aes(x=x,y=value,color=variable))+
geom_line()
}
On 12/31/2013 02:21 AM, Tohamy Yousef wrote:
Hi all,
I need to know how to put a closed frame around my plot. I am
plotting
using the field package, and I have been able to use box() with
limited
success. Box() puts a border around only a part of the
plot area not all.
I saw that there was
Hi,
Try:
ex2 <- function() {
d <- data.frame(x=1:5,a=1:5,b=2:6,c=3:7)
g <- ggplot(d, aes(x))
for (n in c("a","b","c")) {
g <- g + geom_line(aes_string(y=n,colour=n))
}
return(g)
}
A.K.
On Monday, December 30, 2013 7:49 PM, Geoffrey
wrote:
I am trying add geom_line's using a l
I am trying add geom_line's using a loop but the nature of unevaluated
parameters is causing me problems.
This code works:
ex <- function() {
d <- data.frame(x=1:5,a=1:5,b=2:6,c=3:7)
g <- ggplot(d, aes(x))
g <- g +
geom_line(aes(y=a,colour=a)) +
geom_line(aes(y=b,colour=b)) +
g
Dear All,
I want to have the cumulative incidence curves for 'mstate' data using
Survival package in R. But I got some problems:
I. Problem 1:
1. If I only use intercept without any covariates, I can have 'right'
cumulative incidence curves (2 for 2 competing risks):
library(Survival)
fitCI <- sur
Nevermind on this questions, I was able to solve the issue by using
as.dist() instead of dist().
Thanks,
Kerrio
On Mon, Dec 30, 2013 at 2:38 PM, Kerrio Brown wrote:
> Hi,
>
> I'm trying to understand what are the appropriate input for the dist()
> function (
> http://stat.ethz.ch/R-manual/R-pa
Hi all,
I need to know how to put a closed frame around my plot. I am
plotting
using the field package, and I have been able to use box() with
limited
success. Box() puts a border around only a part of the
plot area not all.
I saw that there was a similar problem in this group but I used t
Hi,
i have used rcorr() for calculating pearsons r and according p-values
for my data, giving me 2 matrices.
Now I would like to print scatterplots for all results with "good"
correlation values.
So i need a way to extract the row-name and column-name for each item in
the matrix with "good" r-va
Dear R users,
I have a big problem with R. I want to make a multitaper power spectrum
analysis of a time series using 3 tapers and a resolution of two years with
robust background noise estimation. I try different packages but
unsuccessful.
library(multitaper)
d<-spec.mtm(CAMstd, nw=2, k=3,delta
I don’t know anything about this topic, but looking into this book:
http://books.google.de/books?id=3TVDQBAJ&pg=PA25&lpg=PA25&dq=milliken+and+johnson+unbalanced+machines&source=bl&ots=lxqStiQju5&sig=d5dG_cHsTzilCIklBrW9SAMKYRM&hl=de&sa=X&ei=ifrBUuvoM8qPtAbPqoCQDQ&ved=0CGUQ6AEwBQ#v=onepage&q=mi
Why not using optim on the likelihood in a) with normally distributed standard
errors and for b) optim with a likelihood with t(3)-distributed standard errors?
Best
Simon
On 30 Dec 2013, at 21:19, Xuse Chuse wrote:
> Dear Users,
>
> I am trying to estimate a model Y(t)=alpha+rho*Y(t-1)+e(t)
Dear friends - reading Milliken and Johnson on messy data I failed to
find R code to master the unbalanced Machines data in ch 23.
I wonder if anyone can lend me a hand - again
Happy new year
Troels Ring
Aalborg, Denmark
__
R-help@r-project.org mailing
Dear David--
I think I am straight on the dopiness of my original question.
In trying to make sure I understand your example, I ran this function
below. It seems to assign the value of V from the calling environment to X
as a default, ignored if X is given a value positionally, used if not. It
doe
Dear Bill--
Your final question has my confusion tagged exactly.
Thanks so much for your time and attention!
andrewH
On Sun, Dec 29, 2013 at 5:47 PM, William Dunlap wrote:
> On Dec 28, 2013, at 7:27 PM, Andrew Hoerner wrote:
>
> > Let us suppose that we have a function foo(X) which is called
Dear Users,
I am trying to estimate a model Y(t)=alpha+rho*Y(t-1)+e(t) where i know
e(t)~t(3).
a) I want to estimate (alpha, rho) by QML estimation assuming (wrongly)
that e(t)~N(0,sigma2) and calculate the standard errors.
b) Estimate (alpha, rho) by ML estimation assuming (correctly) e(t)~t(3)
On 13-12-30 2:01 PM, Axel Urbiz wrote:
Thanks for your kind response Duncan. To be more specific, I'm using the
function mvrnorm from MASS. The issue is that MASS depends on survival
and I have a function in my package named tt() which conflicts with a
function in survival of the same name. I can
Thanks for your kind response Duncan. To be more specific, I'm using the
function mvrnorm from MASS. The issue is that MASS depends on survival and
I have a function in my package named tt() which conflicts with a function
in survival of the same name. I can think of 2 alternatives solutions to my
On 13-12-30 1:24 PM, Axel Urbiz wrote:
Dear users,
My package {foo} depends on a function "miscFUN" which is on package
{foo_depend}. This last package also depends on other packages, say {A, B,
C}, but miscFUN is not dependent on A, B, C (only on foo_depend).
In my package {foo}, is there a wa
Thanks a lot!
On Saturday, December 28, 2013 2:54 PM, Jim Lemon wrote:
On 12/29/2013 03:41 AM, capricy gao wrote:
> Really?
>
> OK, here the linked is an example:
>
> http://iai.asm.org/content/77/10/4631/F1.expansion.html
>
>
> Please, any input would be appreciated!
>
>
Hi Capricy,
Reall
Dear users,
My package {foo} depends on a function "miscFUN" which is on package
{foo_depend}. This last package also depends on other packages, say {A, B,
C}, but miscFUN is not dependent on A, B, C (only on foo_depend).
In my package {foo}, is there a way to only have it depend on the function
On Dec 29, 2013, at 10:24 PM, Jeff Newmiller wrote:
You know, Google could have helped you with this question. E.g.
http://r.789695.n4.nabble.com/library-ts-not-available-td3688535.html
fortunes::fortune("'Liaw-Baron principle'")
---
On Dec 29, 2013, at 7:21 PM, Gregory Carey wrote:
Please see the code and R output below. I cannot understand why a
matrix object is being propagated in row major order by default and
then in column major order when byrow=TRUE is specified when I use
one set of dimensions. But when I use d
Hi,
Try:
tab1 <- read.table("132p1vs132p2",sep="\t",header=TRUE)
str(tab1)
#'data.frame': 1765 obs. of 2 variables:
# $ Sample_132p1: num 2.395 0 0.216 0 0.246 ...
# $ Sample_132p2: num 2.428 0 0.247 0 0.136 ...
plot(tab1$Sample_132p1,tab1$Sample_132p2,pch=20)
fm <- lm(tab1$Sample_132p2~ta
Here's one approach. I changed to the graph a bit to include the extremes
of all of the curves, which may or may not be what you want.
Jean
a <- 0.05
b <- 1
kr <- c(70, 60, 50)
K <- kr/a
colz <- c("blue","green","red")
# determine the limits of the graph
maxatx <- kr*b/(2*a)
maxaty <- kr*maxatx
On Sun, Dec 29, 2013 at 11:37 PM, andrewH wrote:
> Dear Ista--
> Peter's post has already persuaded me that my original question was based on
> several misunderstandings and so difficult if not impossible to follow --
> though he did a remarkable job of figuring out where I was going astray and
>
26 matches
Mail list logo
