Hi Marc,
I see what you are saying. I will try re-running the* boot.two.per*
function using 1's and 0's for the data and specifying mean as the
parameter and see what happens. I will report back. Thanks so much for
your kind assistance!
Janh
On Thu, Nov 29, 2018 at 7:07 PM Marc Schwartz wr
Hi,
I don't see Duncan's reply in the archive, but consider:
> 1 / 4
[1] 0.25
> mean(c(1, 0, 0, 0))
[1] 0.25
> 3 / 9
[1] 0.333
> mean(c(1, 1, 1, 0, 0, 0, 0, 0, 0))
[1] 0.333
Regards,
Marc Schwartz
> On Nov 29, 2018, at 6:57 PM, Janh Anni wrote:
>
> Hi Bert,
>
> You mean, just c
Hi Bert,
You mean, just compute the test specifying the mean as the parameter but
using 1's and 0's for the data? Also I don't get how a proportion is a
mean of 0/1 responses. Could you please elaborate? Thanks!
Janh
On Thu, Nov 29, 2018 at 6:45 PM Bert Gunter wrote:
> ... but as Duncan poi
... but as Duncan pointed out already, I believe, a proportion **is** a
mean -- of 0/1 responses.
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Thu, Nov 29,
Hi Rui,
Thanks a lot for responding and I apologize for my late response. I tried
using the *boot.two.per* function in the wBoot package which stated that it
could bootstrap 2-sample tests for both means and proportions but it turned
out that it only works for the mean.
Thanks again,
Janh
On We
Hello,
What have you tried?
Reproducible example please.
http://adv-r.had.co.nz/Reproducibility.html
https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
https://www.r-bloggers.com/minimal-reproducible-examples/
Rui Barradas
Às 22:33 de 27/11/2018, Janh Anni
Hello R Experts!
Does anyone know of a relatively straightforward way to bootstrap
hypothesis tests for proportion in R?
Thanks in advance!
Janh
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and m
Hi R users,
I was struggling to put the results into table format. Would you mind to
show using following data and code how we can put the results into table? I
further would like to have a confidence interval for each group.
set.seed(1000)
data <- as.data.table(list(x1 = runif(200), x2 = runif(
Hi,
After running the bootstrapping, I would like to the output of the bootstrapped
samples. How can I view the bootstrapped samples of each variable?
Bryan Mac
bryanmac...@gmail.com
> On Oct 18, 2016, at 3:57 AM, Rui Barradas wrote:
>
> It means that the sd of the bootstrap samples is 0.21
Hello,
I've just ran your code and it all went well.
So my doubt is: if you have 1269 rows why choose only 100 and
bootstrap? It doesn't seem to make much sense to me.
Try to run the entire df through DataSummary and compare the results
with the bootstrap results.
Rui Barradas
Citando Bry
Hi all,
Here is the first six rows of my data. In total I have 1269 rows.
My goal is to get conduct nonparametric bootstrap and case resampling.
I would like to randomly select 100 out of the 1269 After that, I wish to
bootstrap that randomly selected 100 out of 1269.
I assume I need to set t
Right.
To see it in action just compare the results of the two calls to boot.
library(boot)
set.seed(1007)
x <- rnorm(100)
y <- x + rnorm(100)
dat <- data.frame(x, y)
#Wrong
stat1 <- function(DF, f){
model <- lm(DF$y ~ DF$x, data = DF[f,]) #Doesn't bootstrap DF
coef(model)
}
> On 01 Oct 2016, at 16:11 , Daniel Nordlund wrote:
>
> You haven't told us anything about the structure of your data, or the
> definition of the DataSummary function.
Yes. Just let me add that a common error with boot() is not to pay attention to
the required form of the statistic= function
Dear Rui,
You can insert a “formula” argument in the code. For example, if you boot a
regression, you can insert the formula in the command. Though I just realised
that it is not necessary to do.
All the best,
Christoph
> On 1 Oct 2016, at 19:49, ruipbarra...@sapo.pt wrote:
>
> Sorry, but w
Sorry, but what formula? formula is not a ?boot argument.
To the OP: Michael is probably right, if you reset the seed each time,
you'll get equal values, otherwise you should get different results
due to randomization.
Rui Barradas
Quoting Christoph Puschmann :
Dear Bryan,
Did you try t
Dear Bryan,
Did you try to include formula in the boot command? like:
results <- boot(data, statistic, R, formula)
All the best,
Christoph
> On 1 Oct 2016, at 19:24, Michael Dewey wrote:
>
> Dear Bryan
>
> You are not resetting the seed each time by any chance?
>
> Michael
>
> On 01/10/
On 9/30/2016 6:44 PM, Bryan Mac wrote:
Hi,
I have read the help page and it was helpful but, I am having concerns because
each time I run this code I get the same value.
I expected that each time I run the code, I will get different values due to
random sampling.
How do I get this randomizati
Dear Bryan
You are not resetting the seed each time by any chance?
Michael
On 01/10/2016 02:44, Bryan Mac wrote:
Hi,
I have read the help page and it was helpful but, I am having concerns because
each time I run this code I get the same value.
I expected that each time I run the code, I will
Hi,
I have read the help page and it was helpful but, I am having concerns because
each time I run this code I get the same value.
I expected that each time I run the code, I will get different values due to
random sampling.
How do I get this randomization? The values shouldn’t be the same eac
Hello,
Read the help page ?boot::boot.
For instance, try the following.
library(boot)
x <- rnorm(100)
stat <- function(x, f) mean(x[f])
boot(x, stat, R = 100)
Hope this helps,
Rui Barradas
Citando bryan.mac24 :
Hi all,
I am wondering how to conduct bootstrapping in R. I need bootstrap
Hi all,
I am wondering how to conduct bootstrapping in R. I need bootstrap 100 times.
The trick I need to figure out is how to do get a random sample of 100 out of
the total number of case.
Best,
BM
[[alternative HTML version deleted]]
__
R-hel
Hi
I need a bootstrapping code with ordered categorical data(five categories)
to re-samplling a real data with 16 variables and 200 sample size.
Any help please
--
Thanoon Y. Thanoon
PhD
Department of Mathematical Sciences
Faculty of Science
University Technology Malaysia, UTM
E.Mail: thano
Try
d= data[ ,i]
instead of d= data[i]
in your function. If that doesn't help, I think we would have to know
more about the structure of your data.
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley
I am trying to generate a confidence interval for the statistic arpt (at
risk of poverty threshold generated with the package leaken) using the
package boot.
This is my temptative script (where XH090 and DB030 and w are variables
of an attached dataframe):
> arpt.boot <- function(data,i){
> d
Hello,
I am running a 2 equation system of nonlinear GMM using BFGS in optimx. Using
the conventional way of calculating the standard error of the estimates gives
NAN's for some of the standard errors. As a result, I want to bootstrap the
standard error.
A way forward on how to bootsrap the st
Hi,
I have run a Tukey Kramer on my mixed effects models (using lmer). However,
I have non-normal data that can't really be transformed because it includes
negative numbers. So, I have opted to use a parametric bootstrap to deal
with the violation of the assumptions.
Here is my code for the mixed
Yichun,
1. You are doing this wrong!
2. It is the wrong thing to do!
In more detail:
1. To use boot, it helps to read the help file which clearly says the
statistic must be a function of two arguments, the original dataset and
the indices saying which of the original datapoints are in the boot
Perhaps it should be mentioned that resampling does not produce a
correct CI for extreme quantiles, so the whole exercise may be
pointless.
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certain
Run the examples in the ?boot help page. Notice that boot needs a function that
accepts a dataframe and an index vector.
Sent from my iPhone
> On May 21, 2014, at 1:49 AM, 张以春 wrote:
>
> Dear friends,
>
>
> I have a numeric vector composed of 320 numbers.
>
>
> Now, I want to do resample
Dear friends,
I have a numeric vector composed of 320 numbers.
Now, I want to do resample for 1 times. I want to get maxium number for
every trial and get a 1 maxium numbers.
I have tried to use "boot" package such as follows.
results<-boot(data=nearshore1,statistic=max,R=1,st
Hello,
The jackknife is used as a bias reduction technique, and since linear
regression estimates are unbiased I don't see why you should use it.
Rui Barradas
Em 15-05-2014 19:21, varin sacha escreveu:
Thanks Bert for your suggestion that is working.
To answer to your question, I can say th
Thanks Bert for your suggestion that is working.
To answer to your question, I can say that some econometricians say that using
bootstrap techniques on a linear regression model when the sample size N is
small, one of the most interesting purpose is on the prediction intervals which
is better f
Please note that this can (and should) be considerably sped up by
taking advantage of the fact that lm() will work on a matrix of
responses. Also, some improvement in speed can usually be obtained by
generating all samples at once rather than generating the sample each
time within a loop.
somethin
Hi Rui,
Many thanks for your response.
I have tried to adapt your code to my problem, but there is still a mistake
LinearModel.1 <- lm(GDP.per.head ~ Competitivness.score + Quality.score,
data=Dataset)
B <- 500 # number of bootstrap samples
result <- array(dim = c(22, 3, B))
for(i in 1:B)
{
Hello,
Try to follow the example below and see if you can adapt it to your
needs. Since you don't provide us with a dataset example, I start by
making up some.
# make up some data
n <- 22
set.seed(8873)
dat <- data.frame(x1 = rnorm(n), x2 = rnorm(n))
dat$y <- x1 + x2 + rnorm(n)
B <- 100 #
Dear experts,
>
>
>I have done a multiple linear regression on a small sample size (n=22).
>I have computed the prediction intervals (not the confidence intervals).
>
>
>Now I am trying to bootstrap the prediction intervals.
>
>
>I didn't find any package doing that.
>So I decide to create my own R
Hi R User,
Would you give me some hints on how I can calculate bootstrapping mean+-SE for
each column based by group. I searched it but I could not get what I wanted.
For example I have these data set
data <- as.data.table(list(x1 = runif(200), x2 = runif(200), group =
runif(200)>0.5))
I wante
Thank you for the suggestion. Is there a function for doing that in R?
David
On 3/7/2014 9:50 AM, Therneau, Terry M., Ph.D. wrote:
With respect to question 2, I use the wild bootstrap for tau.
Wu, C.F.J. (1986). Jackknife, bootstrap and other
resampling methods in regression analysis (wi
With respect to question 2, I use the wild bootstrap for tau.
Wu, C.F.J. (1986). Jackknife, bootstrap and other
resampling methods in regression analysis (with discussions).
Annals of Statistics, 14, 1261-1350.
-- begin included message --
I want to bootstrap Kendall's tau corr
I want to bootstrap Kendall's tau correlation with data that have many
NAs. I tried this example:
x <- 1:15
y <- c(2,4,1,3,5, 7,6, 9,10,8, 14, 13, 11, 15, 12)
x[3] <- NA; x[11] <- NA; x[8] <- NA
y[2] <- NA; y[8] <- NA; y[12] <- NA
cor(x,y,use="complete.obs",method="kendall")
library(boot)
tmpdf
Josh's comment prompted me to check mty go-to reference. Davison and
Hinckley (1997 Section 3.8) recommend sampling the Subjects, but not
within the Subjects.
Cheers
Andrew
On Thu, Jul 04, 2013 at 05:53:58PM -0700, Joshua Wiley wrote:
> Hi,
>
> It is not the easiest to follow code, but when I w
Hi,
It is not the easiest to follow code, but when I was working at UCLA,
I wrote a page demonstrating a multilevel bootstrap, where I use a two
stage sampler, (re)sampling at each level. In your case, could be
first draw subjects, then draw observations within subjects. A strata
only option doe
I think that in the case of a 2*2 balanced, replicated design such as
this one, interpreting the interaction should be safe.
Cheers
Andrew
On Fri, Jul 5, 2013 at 9:38 AM, David Winsemius wrote:
>
> On Jul 3, 2013, at 7:19 PM, Sol Lago wrote:
>
>> Hi there,
>>
>> This is the first time I use thi
I'd like to preface this answer by suggesting that if you have multiple
measurements within subjects then you should possibly be thinking about
using mixed-effects models. Here you have a balanced design and seem
to be thinking about a constrained bootstrap, but I don't know whether
the resulting
On Jul 3, 2013, at 7:19 PM, Sol Lago wrote:
> Hi there,
>
> This is the first time I use this forum, and I want to say from the start I
> am not a skilled programmer. So please let me know if the question or code
> were unclear!
>
> I am trying to bootstrap an interaction (that is my test sta
Hi there,
This is the first time I use this forum, and I want to say from the start I am
not a skilled programmer. So please let me know if the question or code were
unclear!
I am trying to bootstrap an interaction (that is my test statistic) using the
package "boot". My problem is that for e
landt
Sent: Thursday, April 25, 2013 4:36 AM
To: Preetam Pal
Cc: r-help@r-project.org
Subject: Re: [R] Bootstrapping in R
On Apr 25, 2013, at 7:02, Preetam Pal wrote:
> Hi all,
>
> 1>i have 3 vectors a,b and c, each of length 25... i want to
> 1>define a
> new data fra
On Apr 25, 2013, at 7:02, Preetam Pal wrote:
> Hi all,
>
> 1>i have 3 vectors a,b and c, each of length 25... i want to define a
> new data frame z such that z[1] = (a[1] b[1] c[1]), z[2] = (a[2] b[2] c[2])
> and so on...how do i do it in R
>
z <- data.frame(a, b, c)
>
> 2> Then i wan
Hi all,
1>i have 3 vectors a,b and c, each of length 25... i want to define a
new data frame z such that z[1] = (a[1] b[1] c[1]), z[2] = (a[2] b[2] c[2])
and so on...how do i do it in R
2> Then i want to draw bootstrap samples from z.
Kindly suggest how i can do this in R.
Thanks,
Preetam
Herbejie Rose,
You could use the boot() function in the R package boot. For example:
# example data matrix
m <- matrix(sample(11*10), ncol=10)
# function to calculate column means for indexed rows of matrix
myfun <- function(data, i) {
apply(data[i, ], 2, mean)
}
# 1000 bootstrap samples
libra
Good evening! This is Herbejie Rose
I need your help for me to compute the following:
I just want to ask on how to bootstrap a 11x10 matrix to obtain 1000
bootstrap samples and compute the 10 dimensional mean per bootstrap sample.
the 11x10 dimension of the matrix has 11 subjects and 10 variable
holas [mailto:cliveli...@googlemail.com]
> *Sent:* Wednesday, November 14, 2012 4:07 AM
>
> *To:* PIKAL Petr
> *Cc:* r-help@r-project.org
> *Subject:* Re: [R] Bootstrapping issues
>
> ** **
>
> Thank you for your answer - I will consult the help file to see if it ha
Hi
Just a copy :-)
Answers please!
Anyway, did my answer resolve your issue?
Petr
From: Clive Nicholas [mailto:cliveli...@googlemail.com]
Sent: Wednesday, November 14, 2012 4:07 AM
To: PIKAL Petr
Cc: r-help@r-project.org
Subject: Re: [R] Bootstrapping issues
Thank you for your answer - I will
listservs - and that perhaps you're being rather
too sensitive in response.
C
On 13 November 2012 12:53, PIKAL Petr wrote:
> Hi
>
> ** **
>
> ** **
>
> *From:* Clive Nicholas [mailto:cliveli...@googlemail.com]
> *Sent:* Tuesday, November 13, 2012 3:12 AM
>
Hi
From: Clive Nicholas [mailto:cliveli...@googlemail.com]
Sent: Tuesday, November 13, 2012 3:12 AM
To: PIKAL Petr
Cc: r-help@r-project.org
Subject: Re: [R] Bootstrapping issues
Petr Pikal replied:
[...]
> The following works
>
> results <- boot(data=test, statistic=bs, R=1000,
Petr Pikal replied:
[...]
> The following works
> >
> > results <- boot(data=test, statistic=bs, R=1000, A~B+C+D+C*D)
> >
>
> Actually it does not work either
>
Correct, but I _did_ get it to work shortly before my initial post (sorry
for not showing it, but I didn't save the output - silly me).
Hi
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Clive Nicholas
> Sent: Monday, November 12, 2012 8:06 AM
> To: r-help@r-project.org
> Subject: [R] Bootstrapping issues
>
> sessionInfo()R ve
sessionInfo()R version 2.15.2 (2012-10-26)
Platform: i686-pc-linux-gnu (32-bit)
locale:
[1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C
LC_TIME=en_GB.UTF-8
[4] LC_COLLATE=en_GB.UTF-8 LC_MONETARY=en_GB.UTF-8
LC_MESSAGES=en_GB.UTF-8
[7] LC_PAPER=C LC_NAME=C
LC_ADDRESS=C
[10] LC_TE
A possiblie solution might be to use the survey package. You could specify
that the data is clustered using the svydesign function, and then speciy the
replicate weights using the as.svrepdesign function. And then, it would be
possible to use the withReplicates function to bootstrap the clusters
A piece of this is solved by the rms package's Rq and bootcov functions.
-Frank
Roger Koenker-3 wrote
> There is no automatic "clustering" option for QR bootstrapping.
> You will have to roll your own.
>
>
> url:www.econ.uiuc.edu/~rogerRoger Koenker
> email
> rkoenker@
>
There is no automatic "clustering" option for QR bootstrapping.
You will have to roll your own.
url:www.econ.uiuc.edu/~rogerRoger Koenker
emailrkoen...@uiuc.eduDepartment of Economics
vox: 217-333-4558University of Illinois
fax: 217-244-66
sry, I forgot to replace rlm() - but actually I tried both and the question
applies to both approaches..
Am 31.10.2012 00:19 schrieb "Kay Cichini" :
>
> HI everyone,
>
> I try to get some bootstrap CIs for coefficients obtained by quantile
regression. I have influencial values and thus switched to
HI everyone,
I try to get some bootstrap CIs for coefficients obtained by quantile
regression. I have influencial values and thus switched to quantreg..
The data is clustered and within clusters the variance of my DV = 0..
Is this sensible for the below data? And what about the warnings?
Thanks
hello,
I am trying to implement the bootstrapping to a set of insurance claim data
in triangular form using the ChainLadder package. I want to obtain the
prediction errors of the reserve estimate using the result from
bootstrapping, here is the output:
>BootChainLadder(Triangle = incr2cum(data)
Hi,
I am doing some bootstrap. This the is the method I am procceding:
I select a value of sigma and set the sharp ratio = 4. From this I can
compute the mean mu.
For a set sample size say n = 11, I generate 999 samples of size 11 with
the sigma and mean above.
This is a 11 x 999 matrix. Now, I
Dear all,
I am currently running an experiment using quantile regression. In order to get
more accurate results for a hypothesis test, I need to run a bootstrapping
version of quantile regression and I need to find the estimated covariance
matrix among all the coefficients for several quantiles
Hi, Let me start my saying that I am new to R hence my grasp of the
appropriate used of R coding is undoubtedly way behind many on this forum.
I am trying to use boostrapping to derive errors around my parameter
estimate for the fixed effects in the following model. It is simply
estimating the num
Hello,
I am having some trouble setting up a bootstrapping prodecure. I create
artificial data and would like to use these to bootstrap a t-test
statistic from these. Especially I do not really get how boot uses the
indices variable or i variable. Can anybody help out? Thanks!!
b0 <- 1/2
On Nov 30, 2011, at 11:31 AM, bubbles1990 wrote:
Hi, Ive been trying to write a program for bootstrapping residuals
in R but
without much success.
A lecturer wants to predict the performance of students in an end-of-
year
physics exam, y. The lecturer has the students results from a mid-
I study a part-time long distance learning course so only really have access
to online sources for help, i'm sure ill crack it eventually. I understand
how to do it with 2 variables, its just having 3 that is confusing me
--
View this message in context:
http://r.789695.n4.nabble.com/Bootstrappin
On Nov 30, 2011, at 11:31 AM, bubbles1990 wrote:
Hi, Ive been trying to write a program for bootstrapping residuals
in R but
without much success.
A lecturer wants to predict the performance of students in an end-of-
year
physics exam, y. The lecturer has the students results from a mid-
Hi, Ive been trying to write a program for bootstrapping residuals in R but
without much success.
A lecturer wants to predict the performance of students in an end-of-year
physics exam, y. The lecturer has the students results from a mid-term
physics exam, x, and a mid-term biology exam, z.
He pr
Your code seems generally ok (though I wonder why you define a function
Var() to do exactly the same thing as var) but your problem is with your use
of mean, not in the bootstrap code.
It collapses things into a vector before taking a mean -- c.f.,
R> x = array(1:27,c(3,3,3))
R> mean(x)
[1] 14
Dear all I am a bit new to R so please keep your swords sheathed!
I would simply like to bootstrap a covariance matrix from a multivariate
gaussian density. At face value that seemed like a very straightforward
problem to solve but I somehow could not get the boot package to work and
did not reall
Hi,
Sorry for repeated question.
I performed logistic regression using lrm and penalized it with pentrace
function. I wanted to get confidence intervals of odds ratio of each
predictor and summary(MyModel) gave them. I also tried to get
bootstrapping standard errors in the logistic regression. boo
On 29.04.2011 09:01, mimato wrote:
I want to classify bipolar neurons in human cochleas and have data of the
following structure:
Vol_Nuc Vol_Soma
1 186.23 731.96
2 204.58 4370.96
3 539.98 7344.86
4 477.71 6939.28
5 421.22 5588.53
6 276.61 1017.05
7 392.28 6392.32
8 424
I want to classify bipolar neurons in human cochleas and have data of the
following structure:
Vol_Nuc Vol_Soma
1 186.23 731.96
2 204.58 4370.96
3 539.98 7344.86
4 477.71 6939.28
5 421.22 5588.53
6 276.61 1017.05
7 392.28 6392.32
8 424.43 6190.13
9 256.41 3850.51
10 24
I have a fair bit of experience with S-Plus and have been asked to port
some of my S-Plus bootstrapping functions to R, to which I am relatively
new, Needless to say, I've run into some problems. In particular, I need
to perform bootstrap resampling of the colMeans function using a moving
block
Dear friends
I want to estimate an equation using two-stage least square but suspect that
the model suffers from autocorrelation. Can someone please advise how to
implement bootstrapping method in order to calculate the correct standard
errors in R? Thank you.
Kind regards
Thanaset
--
View t
In order to bootstrap nonlinear regression, the following code works.
library(nlme)
data(Soybean)
fm1.nls <- nls(weight ~ SSlogis(Time, a, b, c), data=Soybean)
summary(fm1.nls)
bstat <- function(A, indices) {
mboot <- nls(weight ~ SSlogis(Time, a, b, c), data=Soybean[indices, ])
return(coef(mb
On 10/12/2010 08:58 PM, Łukasz Ręcławowicz wrote:
Hi,
I don't know how to sample such data, it can't be done by row sampling
as default method on matrix in boot.
Function takes matrix and returns single coefficient.
#There is a macro but I want use R :)
http://www.comm.ohio-state.edu/ahayes/SP
Hi,
I don't know how to sample such data, it can't be done by row sampling
as default method on matrix in boot.
Function takes matrix and returns single coefficient.
#There is a macro but I want use R :)
http://www.comm.ohio-state.edu/ahayes/SPSS%20programs/kalphav2_1.SPS
library(concord)
librar
On Sep 11, 2010, at 9:50 AM, Gregory Ryslik wrote:
Hi Everyone,
I am implementing a special case of Random forests. At one point, I
have a list of which I then sample for replacement. So if the list
is 100 elements, I get 100 elements some of them duplicates. How can
I easily get the ele
Hi Everyone,
I am implementing a special case of Random forests. At one point, I have a list
of which I then sample for replacement. So if the list is 100 elements, I get
100 elements some of them duplicates. How can I easily get the elements that
were not included in the list? I realize i can
Hello,
Have someone performed a bootstrap in a multiple-mediator model? I am trying to
compute a bootstrap in a multiple and multilevel mediation. Up top now, I have
developed bootstraps in random coeffient models, but I am very lost concerning
the mediation. Could someone to provide me some i
Hello
I am playing around trying to bootstrap an svm model using a training set and a
test set. I've written another function, auc, which I call here, and am
bootstrapping. I did this successfully with logistic regression, but I am
getting an error from the starred ** line which I determined
Thank you for your answer. Sorry for the missing example.
In fact, i think, i solved the issue by some data-manipulations in the
function. I splitted the data (one set for each measuring time), selected the
cases at random, and then combined the two measuring times again. Results look
promisin
On Fri, 16 Apr 2010, Fischer, Felix wrote:
Hello everyone,
i have a question regarding the sampling process in boot().
"PLEASE ... provide commented, minimal, self-contained, reproducible
code." Which means something a correspondent could actually run.
But before that, a careful reading of
Hello everyone,
i have a question regarding the sampling process in boot().
I try to bootstrap F-values for a repeated measures ANOVA to get a confidence
interval of F-values. Unfortunately, while the aov works fine, it fails in the
boot()-function. I think the problem might be that the resampl
Got it.
Thanks
> CC: r-help@r-project.org
> From: dwinsem...@comcast.net
> To: aaron.fo...@students.tamuk.edu
> Subject: Re: [R] bootstrapping
> Date: Wed, 20 Jan 2010 10:34:20 -0500
>
>
> On Jan 20, 2010, at 10:23 AM,
> > wrote:
>
> >
&
.fo...@students.tamuk.edu
CC: r-help@r-project.org
Subject: Re: [R] bootstrapping
Hi Aaron,
try the argument "statistic=mean". Then boot() will give you the mean
turn angle in your actual data (which appears to be 6 degrees,
judging
from what you write), as well as the means of the boot
-project.org
> Subject: Re: [R] bootstrapping
>
> Hi Aaron,
>
> try the argument "statistic=mean". Then boot() will give you the mean
> turn angle in your actual data (which appears to be 6 degrees, judging
> from what you write), as well as the means of
Thanks all for your help!
Aaron
> Date: Sat, 16 Jan 2010 00:04:59 +0100
> From: stephan.kola...@gmx.de
> To: aaron.fo...@students.tamuk.edu
> CC: r-help@r-project.org
> Subject: Re: [R] bootstrapping
>
> Hi Aaron,
>
> try the argument "statistic=mean"
Hi Aaron,
try the argument "statistic=mean". Then boot() will give you the mean
turn angle in your actual data (which appears to be 6 degrees, judging
from what you write), as well as the means of the bootstrapped data.
Then you can get (nonparametric) bootstrap CIs by
quantile(boot$t,probs=c
Hi All,
I'm new to R so please bear with me. I have a dataset with 337 turn angles
ranging from -180 to 180 degrees. I need to bootstrap (sample with
replacement) 1,000 times to create expected average turn angle with 95% CIs.
The code is pretty straightforward (<-boot(data =, statistic
Dear All,
I am trying to bootstrap a large data matrix 'exp' of dimension
9275x898 using package 'boot'. I am trying to calculate correlation of
the obtained samples. I have done following so far:
>library(boot)
>load("ratio_exp.RData") #loading the data matrix
>dim(ratio_exp)
[1] 9275 898
>sampl
Hello
On 1/5/10, Lee William wrote:
> I have got matrix 'data' of dimension 22000x600. I want to make 50
> independent samples of dimension 22000x300 from the original matrix 'data'.
> And then want to calculate pearsons CC for each of the obtained 50 matrices.
> It seems it is possible to do
Hi All,
I have got matrix 'data' of dimension 22000x600. I want to make 50
independent samples of dimension 22000x300 from the original matrix 'data'.
And then want to calculate pearsons CC for each of the obtained 50 matrices.
It seems it is possible to do this using 'boot' function from library b
On Dec 9, 2009, at 9:05 AM, Trafim Vanishek wrote:
I missed number of bootstrap replicates R
boot(Reg, bootcoeff, R=10)
but still it doesn't work
Error in statistic(data, original, ...) : unused argument(s)
(original)
On Wed, Dec 9, 2009 at 2:46 PM, Trafim Vanishek
wrote:
Dear all,
I missed number of bootstrap replicates R
boot(Reg, bootcoeff, R=10)
but still it doesn't work
Error in statistic(data, original, ...) : unused argument(s) (original)
On Wed, Dec 9, 2009 at 2:46 PM, Trafim Vanishek wrote:
> Dear all,
>
> I have some error trying to bootstrap from a matrix. The
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