s/student/faq.html> and
<https://www.amstat.org/ASA/Your-Career/Student-Paper-Competitions.aspx>.
Inquiries and application materials should be sent to:
Patrick Breheny
Department of Biostatistics
University of Iowa
patrick-breh...@uiowa.edu
the awards.
Inquiries and application materials should be sent to:
Patrick Breheny
Department of Biostatistics
University of Iowa
patrick-breh...@uiowa.edu
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.amstat.org/sections/studentpaperawards.cfm
as well as the website of the Statistical Computing Section:
http://stat-computing.org/awards/
Inquiries and application materials should be emailed to:
Student Paper Competition
Patrick Breheny
patrick-breh...@uiowa.edu
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maximum of four supporting letters, each no longer than two pages
Nominations and questions should be sent to the Awards Chair of the
Statistical Computing Section at the e-mail address below.
Patrick Breheny
Department of Biostatistics
University of Iowa
patrick-breh...@uiowa.edu
--
Patri
tings.
Patrick Breheny
Department of Biostatistics
University of Iowa
patrick-breh...@uiowa.edu
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Patrick Breheny
Assistant Professor
Department of Biostatistics
University of Iowa
N336 College of Public Health Building
319-384-1584
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R-help@r-projec
, and the winner(s) will be given an opportunity to
present their work in a topic-contributed session at the meetings.
Patrick Breheny
Department of Biostatistics
University of Iowa
patrick-breh...@uiowa.edu
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Patrick Breheny
Assistant Professor
Department of Biostatistics
University of Iowa
The scales argument in lattice controls the appearance of the axes. It
consists of two lists, one for the x axis and one for the y axis. For
example:
histogram(~pesti[,1]|pesti[,2]+
pesti[,3],scales=list(x=list(at=c(2,6),labels=c("First","Second"
This allows you to place the labels whe
2 2 2 1 NA
_______
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
On 05/04/2011 07:52 AM, Albert-Jan Roskam wrote:
Hello,
A simple question perhaps, but how do I, within each row, find the first
occurence of th
. In other words, this is a linux issue, not an
R issue -- the same thing happens when you use mkdir. This can be
overridden, however. For example,
system("chmod -R 0777 test")
which recursively changes the mode of test and all its subdirectories
from within R.
_____
.
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Patrick Breheny
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Department of Statistics
University of Kentucky
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PLEASE do read the posting guide http://www.R
ance for your help
Best Regards
Alex
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Department of Statistics
University of Kentucky
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;)))
sapply(x,'[[',"Two")
[,1] [,2]
[1,] "b" "e"
[2,] "c" "f"
In your example, it seems
sapply(CRagentInTime[[1]][[2]],'[[',"sr")
would work, but I am not in a position to replicate your code, as is it
not s
x[[1]][[2]], not
c(x[[1]], x[[2]]).
Thank you for the clarification; I stand corrected.
___
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
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R-help@r-project.org ma
E),]
aa bb
10 j -2.21178676
9 i -0.52119533
8 h 0.80990322
7 g 2.44362935
6 f 3.16449690
5 e -0.33932586
4 d -0.86918700
3 c -1.86750927
2 b -0.65623164
1 a 0.06365513
The expression 'df1[,-2]' removes the second column from df1; clearly
not what you
You have 5 variables. Variable selection is not your goal. What you
are trying to do is fit a curve (as opposed to a line) through your
data, along possibly with interactions. I would suggest looking into
splines, provided for example in the mgcv package.
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Patrick Breheny
Assistant Prof
go into greater detail about what you are trying to
accomplish with this line of code.
Also, probably not a good idea to have a variable called 'c', as this is
bound to lead to confusion with the function for combining objects, 'c()'.
--
Patrick Breheny
Assistant
You could try:
f <- function(x){pnorm(x,mean=10,sd=20)}
curve(f,from=-10,to=30)
Or:
x <- seq(-10,30,len=101)
y <- pnorm(x,mean=10,sd=20)
plot(x,y,type="l")
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
comparison:
plot(ecdf(x),add=TRUE,do.points=FALSE,verticals=TRUE)
Please be aware, however, that density estimation is a complicated topic
with an extensive literature.
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
Univer
ou take the advice of point 1) and put an intercept in your model.
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Department of Statistics
University of Kentucky
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On 08/10/2011 03:00 AM, Nick Sabbe wrote:
Finally, to avoid downward bias, you could run a normal glm with only the
variables selected in the previous step.
At the cost, of course, of introducing upward bias
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Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of
;externally studentized residuals"). There is a closed form
expression, but it is somewhat bulky.
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Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
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ot have an observation in each class in each
fold. It would be rather difficult to estimate the probability of
belonging to a class without any data.
2) Do you really hope to obtain a meaningful fit for a multinomial model
with only 8 observations? How many classes do you have?
--
Patri
#x27;p-value' would simply be the fraction of cases in
your sample as large or larger than the observation in question.
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
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R
On 09/02/2011 08:48 AM, John Sorkin wrote:
I believe when using BIC one needs to compare nested models
This is wrong. Hypothesis tests rely on nested models; information
criteria do not.
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Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University
; my remark was only meant to refer to the simple case of
logistic regression in the original post, and certainly should not be
construed as a blanket statement applying to all possible hypothesis
tests of all possible models.
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
tion rate is
> 1-sum(diag(tab))/sum(tab)
[1] 0.54
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Assistant Professor
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Department of Statistics
University of Kentucky
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PLE
m is the number of random vectors you wish to generate in this manner.
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University of Kentucky
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y~X)
plot(fit)
The latter type of plot is called a "partial regression plot" or "added
variable plot". They are discussed in any regression textbook, as well
as wikipedia and probably dozens of other web sites.
--
Patrick Breheny
Assistant Professor
Department of Bios
On 09/14/2011 11:36 AM, David Winsemius wrote:
On Sep 14, 2011, at 10:52 AM, Patrick Breheny wrote:
The latter type of plot is called a "partial regression plot" or
"added variable plot". They are discussed in any regression
textbook, as well as wikipedia and probably dozen
matrices, this and other operations will be
faster if the matrix is explicitly stored as a sparse matrix, as
implemented in the 'Matrix' package.
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
_
isting of only the first 8 observations, then all the columns.
Perhaps you mean:
X <- crs[,1:8]
y <- crs[,9]
If this is not the case, please include the output of
head(crs)
and then tell us which variable is your response.
--
Patrick Breheny
Assistant Professor
Department of B
ger than usual? If so, and you
suspect a problem with the way that glmnet is partitioning the data set
into cross-validation folds, you can specify that with the 'foldid' option.
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
Univ
putational convenience when n is large, which is not a large problem
in your case.
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Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
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threshold.
Am I running my code wrong?
Your code is fine; your conclusion is valid (assuming you mean
"...better than site 1...").
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Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
___
is leading to the fitted
probabilities near 0 and 1 you are observing (note that only 0.1% of the
data is in region 4 above, although region 4 accounts for 99.1% of the
range of x).
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
ulate:
X <- matrix(rnorm(100*10),ncol=10)
y <- X%*%c(rep(2,5),rep(0,5))+rnorm(100)
fit <- ctree(y~.,data=as.data.frame(X))
r <- y - predict(fit)
1-var(r)/var(y)
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of S
glm<- glm(cbind(SUCCESSESS,TRIALS) ~ INDEP1 + INDEP2 +
INDEP3, data = data,family = binomial)
as is specified in the details of ?glm.
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
__
onus only has 7 unique values. Claims does not pose any problem, as it
has 98 unique values. As Jean suggested, you can get around this issue
with:
amgam<- gam(log(Payment) ~ offset(log(Insured)) +
s(as.numeric(Kilometres),k=5) + s(Bonus,k=7) + Make + s(Claims),family =
gaussian, dat
it object so I
can do 'stuff' with it?
Thanks,
Ben
PS - thank you Patrick for your help previously.
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PLEASE do read th
fit-1.96*pred$se.fit)
u <- binomial()$linkinv(pred$fit+1.96*pred$se.fit)
plot(x,yy,type="l")
lines(x,l,lty=2)
lines(x,u,lty=2)
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
On 03/14/2012 01:49 PM, Ben quant wrote:
repeatedly manipulate it as though
its rows are scalars
* you're missing a negative in the normal likelihood.
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Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
On 03/14/2012 01:21 PM, Michael Williams wrote:
Hi all,
I'm
There are a few different ways to do this; see the examples in ?plotmath
under the heading "How to combine 'math' and numeric variables".
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Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
On 03/20/2012 09:09
ot believe that is possible with the current implementation of
glmnet. The glmnet() function includes an intercept by default and
there are no options which allow the user to change this.
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University o
, it is impossible to know in advance how fine the grid must be
in order to ensure that only one variable enters the model between any
two consecutive lambda values.
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Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Statistics
University of Kentucky
_
, but not for the median:
A =c(619, 600, 490, 1076, 654, 955, 563, 955, 827, 873, 1253)
B =c(346, 507, 598, 228, 576, 338, 1153, 354, 560, 517, 381)
> median(A)-median(B)
[1] 320
> median(A-B)
[1] 273
--
Patrick Breheny
Assistant Professor
Department of Biostatistics
Department of Stat
To give a little more detail, you can convert your character strings
into POSIX objects, then extract from it virtually anything you would
want using strftime. In particular, %W is how you get the week number:
> dateRange <- c("2008-10-01","2008-12-01")
> x <- as.POSIXlt(dateRange)
> strftime(
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