Displaying 20 results from an estimated 1000 matches similar to: "Mininum number of resamples required to do BCa bootstrap?"
2012 Oct 02
0
Possible error in BCa method for confidence intervals in package 'boot'
I'm using R 2.15.1 on a 64-bit machine with Windows 7 Home Premium.
Sample problem (screwy subscripted syntax is a relic of edited down a
more complex script):
> N <- 25
> s <- rlnorm(N, 0, 1)
> require("boot")
Loading required package: boot
> v <- NULL # hold sample variance estimates
> i <- 1
> v[i] <- var(s) # get sample variance
>
2007 Oct 18
0
Getting 'tilting' confidence intervals in R
I am trying to compute bootstrap confidence intervals for a sample
using R 2.5.1 for Windows.
I can get "Normal", "Basic", "Percentile", "BCa" and "ABC" from
boot.ci() and boot() in the Davison & Hinkley "boot" package.
But I can't figure out how to use tilt.boot() to get the "tilting"
confidence interval.
2007 Oct 18
0
[R} Getting 'tilting' confidence intervals in R
[Resend with proper subject line]
I am trying to compute bootstrap confidence intervals for a sample
using R 2.5.1 for Windows.
I can get "Normal", "Basic", "Percentile", "BCa" and "ABC" from
boot.ci() and boot() in the Davison & Hinkley "boot" package.
But I can't figure out how to use tilt.boot() to get the
2008 Sep 26
0
Confidence interval for binomial variance
Based on simulations, I've come up with a simple function to compute
the confidence interval for the variance of the binomial variance,
where the true variance is
v = rho*(1-rho)/n
where rho = true probability of success and n = # of trials.
For x = # successes observed in n trials, p = x / n as usual.
For p < 0.25 or p > 0.75, I use the proportion-based transformed
confidence
2013 Mar 12
1
Bootstrap BCa confidence limits with your own resamples
I like to bootstrap regression models, saving the entire set of bootstrapped
regression coefficients for later use so that I can get confidence limits
for a whole set of contrasts derived from the coefficients. I'm finding
that ordinary bootstrap percentile confidence limits can provide poor
coverage for odds ratios for binary logistic models with small N. So I'm
exploring BCa confidence
2007 Sep 10
1
S-Plus "resample" package and associated functions
Are there any packages in R that reproduce the package "resample" of S-Plus?
The sample() function in R doesn't provide equivalent flexibility of
bootstrap() and bootstrap2().
================================================================
Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: ral at lcfltd.com
Least Cost Formulations, Ltd. URL: http://lcfltd.com/
824
2011 Sep 20
0
The boot Package with bca Intervals and Inf and NaN Values in an Automated Function [mediation()]
Hi everyone,
I use the boot package within the MBESS package to automate much of
the hard part for folks interested in performing a (simple) mediation
model. The function mediation() works well, except for a (probably)
unrealistic artificial data set.
When I apply the bootstrap I sometimes get:
Error in t.star[r, ] <- res[[r]]
which is (I think) due to Inf and -Inf and NaN values produced for
2006 Jun 28
2
Problem searching with special characters
I''m using Ferret on a Swedish website and I get some unexpected
behaviour on searches containing the swedish charchters ???.
An exampel, if I index a string "Varf?r fungerar det inte" ("Why doesnt
it work" in swedish) and search for "f?r" I''ll get one (1) match. The
expected behaviour would be no matches since ''f?r'' is part of
2008 Sep 25
1
R function which finds confidence interval for binomial variance
I need to construct confidence intervals for the binomial variance.
This is the usual estimate
v = x*(n-x)/n
or its unbiased counterpart
v' = x*(n-x)/(n-1)
where x = binomial number of successes observed in n Bernoulli trials
from proportion p.
The usual X^2 method for variance confidence intervals will not work,
because of the strong non-normal character of the sampling
2010 Jun 21
2
Singularity in simple ANCOVA problem
I'm using R 2.10.1 with the latest version of all packages (updated today).
I'm confused as to why I'm getting a hard singularity in a simple set
of experimental data:
> blots
ID Lot Age Conc
1 1 A 3 4.44
2 2 A 3 4.56
3 3 B 41 4.03
4 4 B 41 4.57
5 5 C 229 4.49
6 6 C 229 4.66
7 7 D 238 3.88
8 8 D 238 3.93
9 9 E 349 4.43
10 10 E 349
2009 Sep 03
1
Problem accessing functions in package 'roxygen'
I have Vista Home with R-2.9.0, and installed and tried to test the
package 'roxygen':
> utils:::menuInstallPkgs()
trying URL
'http://lib.stat.cmu.edu/R/CRAN/bin/windows/contrib/2.9/roxygen_0.1.zip'
Content type 'application/zip' length 699474 bytes (683 Kb)
opened URL
downloaded 683 Kb
package 'roxygen' successfully unpacked and MD5 sums checked
The
2008 Mar 08
1
How to do multi-factor stratified sampling in R
Given a set of data with a number of variables plus a response, I'd
like to obtain a randomized subset of the rows such that the marginal
proportions of each variable are maintained closely in the subset to
that of the dataset, and possibly maintaining as well the two-factor
interaction marginal proportions as well for some pairs.
This must be a common problem in data mining, but I
2009 Jul 02
1
Getting identify() to work with lattice::cloud()
I don't seem to be able to put any syntax into identify() that gets
it to work with "lattice" cloud() graph:
layout(1)
require('lattice')
cloud(g3 ~ g1 + g2, data=gapp, col = "blue",
xlab='G1 Score', ylab='G2 Score',
zlab='G3 Score', main='3D Plot for Applicants')
identify(gapp[,2:4], labels=gapp$ID)
Here g1 is gapp[,2], g2
2008 Apr 22
2
Multidimensional contingency tables
How does one ideally handle and display multidimenstional contingency
tables in R v. 2.6.2?
E.g.:
> prob1<- data.frame(victim=c(rep('white',4),rep('black',4)),
+ perp=c(rep('white',2),rep('black',2),rep('white',2),rep('black',2)),
+ death=rep(c('yes','no'),4), count=c(19,132,11,52,0,9,6,97))
> prob1
victim perp
2007 Nov 07
2
creating a dynamic output vector
Let's say I have a program that returns variables whose names may be any
string within the vector
NAMES=c("varA","varB","varC","varD","varE","varF"..."varZ"), but I do
not ever know which ones have actually been created. So in one example
output, "varA", "varC", and "varD" could exist, but
2008 Apr 10
1
Problem installing and using package "tseries"
I have R 2.6.2, and have tried downloading and installing the package
"tseries". I get the same error when I use two different mirror sites:
> utils:::menuInstallPkgs()
trying URL
'http://cran.mirrors.hoobly.com/bin/windows/contrib/2.6/tseries_0.10-14.zip'
Content type 'application/zip' length 400799 bytes (391 Kb)
opened URL
downloaded 391 Kb
package
2007 May 27
1
How to reference or sort rownames in a data frame
As I was working through elementary examples, I was using dataset
"plasma" of package "HSAUR".
In performing a logistic regression of the data, and making the
diagnostic plots (R-2.5.0)
data(plasma,package='HSAUR')
plasma_1<- glm(ESR ~ fibrinogen * globulin, data=plasma, family=binomial())
layout(matrix(1:4,nrow=2))
plot(plasma_1)
I find that data points
2007 Jul 23
0
Conditional logistic regression on n:m matched "cohort" data
I am designing an interlaboratory validation study for a
presence/absence alternative method test kit vs. a presence/absence
reference method test kit.
There will be 10 laboratories conducting tests using both methods. In
each laboratory, there will be 5 specimens tested, each of the 5
specimens twice by both methods (alternative, standard).
The total number of data are 10 x 5 x 4 = 200.
2007 Jun 08
1
glm() for log link and Weibull family
I need to be able to run a generalized linear model with a log() link
and a Weibull family, or something similar to deal with an extreme
value distribution.
I actually have a large dataset where this is apparently necessary.
It has to do with recovery of forensic samples from surfaces, where
as much powder as possible is collected. This apparently causes the
results to conform to some type
2007 Apr 25
0
Use of Lexis function to convert survival data to counting format
I'm trying to convert a dataset from the time-independent analysis form
> head(addicts)
id clinic status survtime prison meth clinic01
1 1 1 1 428 0 50 1
2 2 1 1 275 1 55 1
3 3 1 1 262 0 55 1
into the "counting data format" necessary to perform extended Cox regression.
I got