>On Tue, 4 Sep 2007, [EMAIL PROTECTED] wrote:
>> I am new to R. I would like to calculate bootstrap confidence intervals
>> using the BCa method for a parameter of interest. My situation is this: I
>> already have a set of 1000 bootstrap replicates created from my original
>> data set. I have alrea
On Tue, 4 Sep 2007, [EMAIL PROTECTED] wrote:
> Dear R users,
>
> I am new to R. I would like to calculate bootstrap confidence intervals
> using the BCa method for a parameter of interest. My situation is this: I
> already have a set of 1000 bootstrap replicates created from my original
> data set
Dear R users,
I am new to R. I would like to calculate bootstrap confidence intervals
using the BCa method for a parameter of interest. My situation is this: I
already have a set of 1000 bootstrap replicates created from my original
data set. I have already calculated the statistic of interest
Dear R users,
I'm having some problems trying to create a routine for a bootstrap
resampling issue. Suppose I've got a dataset like this:
Header inr weeks .
12800012.47 0 ...
12800011.48 1 ...
1280001
Dear R users,
I'm having some problems trying to create a routine for a bootstrap
resampling issue. Suppose I've got a dataset like this:
Header inr inf .weeks ...
insideaboveunder
12800012.75 2.5 ..0
1
t by: r-help@stat.math.ethz.ch
[EMAIL PROTECTED] cc
at.math.ethz.ch
Subject
Dear All,
I would like to use a nonparametric bootstrap to calculate the confidence
intervals for the 5% and 95% quantiles using boot.ci. As you know, boot.ci
requires the use of boot to generate bootstrap replicates for my statistic.
However this last function doesn't work in my case bec
On Sat, 31 Mar 2007 10:59:37 -0700 (PDT), Tarik wrote:
> My dissertation on bootstrapping linear time series models,
> I mainly use R language, however, I must confess that I find it
> difficult to bootstrap moving average models and ARMA models ,
> therefore I would be very grateful if y
Hi everyone,
Currently I work for Master degree
in statistics at Garyounis University.
My dissertation on bootstr
Indermaur Lukas wrote:
> Hi,
> I would like to evaluate the frequency of the variables within the best
> selected model by AIC among a set of 12 competing models (I fit them with
> GLM) with a bootstrap procedure to get unbiased results. So I would ike to
> do the ranking of the 12-model-set 10
Hi,
I would like to evaluate the frequency of the variables within the best
selected model by AIC among a set of 12 competing models (I fit them with GLM)
with a bootstrap procedure to get unbiased results. So I would ike to do the
ranking of the 12-model-set 10'000 times separately and calcula
Previous subject:
bootstrap bca confidence intervals for large number of statistics in one model;
library("boot")
Jacob Wegelin asked for an easier way to do many bootstrap confidence
intervals for regression output.
The syntax would be easier with S+Resample, example below.
You create an ordinar
Sometimes one might like to obtain pointwise bootstrap bias-corrected,
accelerated (BCA) confidence intervals for a large number of statistics
computed from a single dataset. For instance, one might like to get
(so as to plot graphically) bootstrap confidence bands for the fitted
values in a regr
Dear R-friends,
I have a table data structured by group, subgroups, records and attributes.
For each group and subgroup I have differente number of records (more than
200). I need bootstrap 100 records for each group/subgroup combinations and
repeat it a big number of times.
Could so
Hello everyone.
I have 6 to 10 strata with 6 to 12 subject within each stratum. I will
like to do bootstrap to compute a confidence interval for an estimator
which is a function of the Wilconson sum rank test. Are there any function
in R to do this? Any reference will be helpful.
Thank you
To
Hi,
I have some problems I have a Cauchy distribution with density function
f(x) = sigma / (pi * (sigma^2 + (x- miu)^2) ),
where sigma = scale and miu = location (in my case sigma = 3, miu = 0), and I
have to find with bootstrap
E | sigma_estimated^3 sigma^3 | (#),
I am not sure I understand what you want to do, but maybe some of this
will be helpful. I first generate some data that should resemble yours:
dat<-expand.grid(Region=1:3, Species=1:4, Sex=c("M","F"))
dat<-do.call("rbind",lapply(1:10,function(x) dat))
dat$Bodysize<-rnorm(nrow(dat),10,2)
Now what
Hi R-friends.
I have a mammal´s dataset looking like:
Region Species Sex Bodysize
1 Sp1 M 10.2
1 Sp1 M 12.1
1 Sp1 M 9.1
...
I have three regions, four species and the body size
Dear R People
I´m student of master in statistic and data analysis. I did use R (SURVEY
Package) to estimate sampling variance. The data is come from Incoming and
Expendure Survey in Maputo City (Mozambique) careout by National Statistic
Institute of Mozambique, from June 2002 to July 2003 . T
weights : num [1:10] 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
- attr(*, "class")= chr "boot"
Andy
-Original Message-
From: Michael [mailto:[EMAIL PROTECTED]
Sent: Thursday, April 20, 2006 12:19 PM
To: Liaw, Andy
Cc: R-help@stat.math.ethz.ch
Subject: Re: [R] Bootstrap erro
00, stype='w');
>
> The result is zero:
>
> Bootstrap Statistics :
> original biasstd. error
> t1* 2.305412 0 0
>
>
> On 4/20/06, Liaw, Andy <[EMAIL PROTECTED]> wrote:
> >
> > > -Original Message-
> > > Fr
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Michael
> Sent: Thursday, April 20, 2006 3:50 AM
> To: R-help@stat.math.ethz.ch
> Subject: [R] Bootstrap error message: Error in
> statistic(data, original, ...) : unused argument
Dear colleagues,
I've been swamped and fighting with error for a few hours but still
desperately having absolutely no clue:
What's wrong with my bootstraping code?
Thanks a lot!
Error Message:
> bootResults=boot(X, myFun, R=1);
Error in statistic(data, original, ..
On Tue, 11 Apr 2006, Carlos Creva Singano (M2004078) wrote:
Dear R users,
I´m student of Master in Statistic and Data analysis, in New University
of Lisbon. And now i´m writting my dissertation in variance
estimation.So i´m using Survey Package to compute the principal
estimators and theirs
Carlos Creva Singano (M2004078) wrote:
>
> 1. How to compute Bootstrap and Jackknife Bias of estimates, like mean?
Have you had a look at packages "boot" and "bootstrap"? E.g. you can
compute the bias and s.e. of an estimate theta using bootstrap
library("boot")
a <- boot( data, theta, R=1000 )
Dear R users,
I´m student of Master in Statistic and Data analysis, in New University of
Lisbon. And now i´m writting my dissertation in variance estimation.So i´m
using Survey Package to compute the principal estimators and theirs variances.
My data is from Incoming and Expendire Survey. This
Looks like I may have found a function that addresses my needs. Bootcov in
Design handles bootstrapping from clustered data and will save the
coefficients. I'm not entirely sure it handles clusters the way I'd like,
but I'm going through the code. If it doesn't, it looks easily
re-writeable. As
Are there any functions in R for running bootstraps with clustered (as
opposed to stratified) data? I can't seem to find anything obvious in boot
or Bootstrap, though I imagine boot can be manipulated to resample from
clusters. Is that what people use?
I do see some cluster bootstrap resampling
Dan Janes oeb.harvard.edu> writes:
>
> Hi all,
> I am trying to bootstrap a small data set into 1000 "pseudodatasets" and
> then run an ANOVA on each one. Can anyone provide guidance on how I could
> do this?
>
> Thank you.
>
> -Dan Janes
>
> ***
Hi all,
I am trying to bootstrap a small data set into 1000 "pseudodatasets" and
then run an ANOVA on each one. Can anyone provide guidance on how I could
do this?
Thank you.
-Dan Janes
Dan Janes, Ph.D.
Harvard University/OEB
26 Oxford St.
C
essage-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of
> Christoph Lehmann
> Sent: Sunday, April 24, 2005 12:48 PM
> To: Peter Soros
> Cc: r-help@stat.math.ethz.ch
> Subject: Re: [R] Bootstrap / permutation textbooks
>
> look at:
>
>
look at:
AC Davison, DV Hinkley: Bootstrap Methods and Their Applications
there is also a R-library 'boot', based on methods reported in this book
C
Peter Soros wrote:
Dear R experts,
I would like to explore if and to what extent bootstrapping and
permutation statistics can help me for my research
Dear R experts,
I would like to explore if and to what extent bootstrapping and
permutation statistics can help me for my research (functional brain
imaging). I am looking for an introductory textbook, rather legible. I
have statistical knowledge, but I am definitely no statistical or
mathemati
t for your
case as well.
Reid Huntsinger
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of array chip
Sent: Wednesday, April 06, 2005 1:19 PM
To: r-help@stat.math.ethz.ch
Subject: [R] bootstrap vs. resampleing
Hi,
I understand bootstrap can be used to e
Confidence intervals depend on the sample size - the bigger the sample the
smaller the interval. Subsampling (resampling without replacement) gives
smaller samples and underestimates confidence (overestimates confidence
interval size) of parameters calculated on the original sample.
Best
Jens O
On Wed, 6 Apr 2005, array chip wrote:
Hi,
I understand bootstrap can be used to estimate 95%
confidence interval for some statistics, e.g.
variance, median, etc. I have someone suggesting that
by resampling certain proportion of the total samples
(e.g. 80%) without replacement, we can also get the
What you're describing sounds like subsampling, about which John
Hartigan has written a few papers.
-roger
array chip wrote:
Hi,
I understand bootstrap can be used to estimate 95%
confidence interval for some statistics, e.g.
variance, median, etc. I have someone suggesting that
by resampling cer
> Sent: Wednesday, April 06, 2005 10:19 AM
> To: r-help@stat.math.ethz.ch
> Subject: [R] bootstrap vs. resampleing
>
> Hi,
>
> I understand bootstrap can be used to estimate 95%
> confidence interval for some statistics, e.g.
> variance, median, etc. I have someone
Hi,
I understand bootstrap can be used to estimate 95%
confidence interval for some statistics, e.g.
variance, median, etc. I have someone suggesting that
by resampling certain proportion of the total samples
(e.g. 80%) without replacement, we can also get the
estimate of confidence intervals. Her
On Sat, 19 Feb 2005, j h wrote:
Please, can you help me with a problem concerning bootstrap. I have a
2 by 20 matrix. I want to define each row as a variable. Then using
bootstrap to calculate standard errors, confidence intervals, and
significance tests. How can I do from defining the varia
Dear R community,
Please, can you help me with a problem concerning bootstrap. I have a 2 by
20 matrix. I want to define each row as a variable. Then using bootstrap to
calculate standard errors, confidence intervals, and significance tests. How
can I do from defining the variables to boot
Hello,
I have several ordered groups (20), each with several observations. Each
group has fewer observations roughly linearly from 30 to 0. Each
observation is a proportion. As I know the max and min values for a
proporion are 1 and 0, I am adding these values to each group to allow
bootstrap fo
Fredrik Lundgren wrote:
Hello R'ers
In previous versions of R (I now use 2.0.1) there was a package
"bootstrap". I wrote some programs that depended heavily on this
package but can unfortunately not find it on Cran today. Is there any
way to find an older version of "bootstrap" and use it with t
Fredrik Lundgren wrote:
Hello R'ers
In previous versions of R (I now use 2.0.1) there was a package
"bootstrap". I wrote some programs that depended heavily on this package
but can unfortunately not find it on Cran today. Is there any way to
find an older version of "bootstrap" and use it with t
On Mon, 13 Dec 2004, Kjetil Brinchmann Halvorsen wrote:
> Fredrik Lundgren wrote:
>
> > Hello R'ers
> >
> > In previous versions of R (I now use 2.0.1) there was a package
> > "bootstrap". I wrote some programs that depended heavily on this
> > package but can unfortunately not find it on Cran tod
Fredrik Lundgren wrote:
Hello R'ers
In previous versions of R (I now use 2.0.1) there was a package
"bootstrap". I wrote some programs that depended heavily on this
package but can unfortunately not find it on Cran today. Is there any
way to find an older version of "bootstrap" and use it with t
Hello R'ers
In previous versions of R (I now use 2.0.1) there was a package
"bootstrap". I wrote some programs that depended heavily on this package
but can unfortunately not find it on Cran today. Is there any way to
find an older version of "bootstrap" and use it with the new version -
2.0.1?
Hi there. OSX/R2.0
We are trying to implement a bootstrap of the coeffecients of a mixed
effect model. In particular, we are interested in the intercept and
slope of the random effects.
Following from the basics for a linear model, we construct our lme
models and a boot function:
library(n
Hi
I need to bootstrap a function in R and I am
struggling. Can anyone help? The following explains
what Im trying to do:
I have 2 different matrices, called x and y. Each
has 34 columns, and the length of each column varies.
I use this data to determine a certain measure (C),
which Ive c
did you look at library(boot) ?boot
On 9/22/04 9:19 AM, "nmi13" <[EMAIL PROTECTED]> wrote:
> Dear Any,
>
> Can someone please inform me, if they have a code to estimate the varaince
> using bootstrap resampling method under a two stage cluster design.
>
> Thanks for all your help and time.
>
>
Dear Any,
Can someone please inform me, if they have a code to estimate the varaince
using bootstrap resampling method under a two stage cluster design.
Thanks for all your help and time.
Murthy.M.N.,
PhD, Student,
University of Canterbury,
New Zealand.
Have you considered "simulate.lme" in package nlme? This is not
bootstrapping, but it's not obvious to me how to bootstrap with a
complicated structure and get anything with a simple interpretation.
More information on this is provided in Pinhiero and Bates (2000)
Mixed-Effects Models in
Paul,
I think that you should account for the group structure.
My reading of Davison and Hinkley "Bootstrap Methods and their
Application" (1997, p. 100) suggests that for balanced data structures
with more than, say, 10 clusters, one should apply the bootstrap to
the clusters, but not within the
I would appreciate some thoughts on using the bootstrap functions in the
library "bootstrap" to estimate confidence intervals of ICC values
calculated in lme.
In lme, the ICC is calculated as tau/(tau+sigma-squared). So, for instance
the ICC in the following example is 0.116:
> tmod<-lme(CINISMO
Is there an R-procedure to calculate a Kaplan Meier estimate with
confidence bounds for correlated survival times (with correlated groups of
observations which can be accounted for with the "cluster" argument in the
cox regression). I would need it to estimate the survival time of dental
impla
1. Have you studied the documentation, including working the
examples, for "nls" and "boot"? I don't see "data" as an argument to
"nls", as I'm used to, and your use of "i" also seems disconcerting to
me. Something like the following seems to me to be closer to the
standard syntax and t
Hi,
I am trying to bootstrap the difference between each parameters among two non linear
regression (distributed loss model) as
following:
# data.frame
> Raies[1:10,]
Tps SolA Solb
10 32.97 35.92
20 32.01 31.35
31 21.73 22.03
41 23.73 18.53
52 19.68 18.28
62 18.56 16
Dear All,
I was writing a small wrapper to bootstrap a classification algorithm, but if
we generate the indices in the "usual way" as:
bootindex <- sample(index, N, replace = TRUE)
there is a non-zero probability that all the samples belong to only
one class, thus leading to problems in the fi
Package bootstrap is ORPHANED (that is, unsupported by anyone). Do try
package boot instead.
10 is a very small number of bootstrap replications: I do suggest you try
100 or more.
On Fri, 9 Apr 2004, Michaël Coeurdassier wrote:
> Dear R community,
>
> Please, can you help me with a problem
Dear R community,
Please, can you help me with a problem concerning bootstrap. The data table
called «RMika», contained times (Tps) and corresponding concentration of a
chemical in a soil (SolA). I would like to get, by bootstraping, 10
estimations of the parameters C0 and k from the function:
Dear listers,
I would like to get the bootstrap estimates form my lme model.
I have an HLM (multillevel) 2-level model with the dichotomous outcome. I
used glmmPQL procedure. However I have a problem since I have a rather
unbalanced proportion (90-99% of events, i.e. ones and only 1-10% of
noneve
Hello R-List
I use DClusters package (I work in a cancer regestry). I have 2 questions
about it:
1-how is it possible to get back the bootstrap pValue? I mean the pValue of
the calculated statistic with respect of the distribution of this statistic
under the null hypothesis.
2-how is it possible
I have a question regarding bootstrap coverage. I am trying to understand the
benefits of using the bootstrap for small sample sets. To do this I created a normal
population and then picked 10 from the populations and applied both traditional
statistical methods and the Bootstrap (bcanon, 5000
Hello,
I am trying to bootstrap the following statistic:
1- x/y
using different sample sizes for x and y (x and y are not paired data).
Apparently, only one sample size can be handled, and the na.action
(na.exclude) does not work with boot.
Could anyone help ?
thanks a lot
Marie-Agnès Coutellec
http://www.anu.edu.au/cmhr/
[EMAIL PROTECTED] +61 (2) 6125 3379
> -Original Message-
> From: Ron Ophir [mailto:[EMAIL PROTECTED]
> Sent: Monday, 14 July 2003 5:10 AM
> To: [EMAIL PROTECTED]
> Subject: [R] bootstrap for hclust
>
>
> dear group members,
> I am looking
dear group members,
I am looking for a function that assess the stability of cluster. The result of hclust
function is an hclust object which can be plot as a dendrogram. However to have
confidence in the tree topology usualy bootstap is applied. I understand that I can
apply bootstarp on the o
You are using the boot function incorrectly. This is taken from the
help page:
statistic: A function which when applied to data returns a vector
containing the statistic(s) of interest. When
`sim="parametric"', the first argument to `statistic' must be
the data. F
Dear r People
I have a bootstrap question, please.
(this may possibly be a problem with my understanding of the bootstrap)
Suppose I have a sample of size 15, x[1], ...x[15].
This is a sample which is small compared to the population.
by the way, the x[i] are iid and have a common distributio
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