Hi all,
I'd like to calculate confidence intervals around Aalen-Johansen
estimates at given time points. And later I'd like to be able to
compare the Aalen-Johansen estimates at given time points between
groups.
My problem is, that there are no events recorded.
So my question is:
Does anyone kno
Hi Jim:
Thank you very much for your help in this topic.
with many thanks
abou
__
*AbouEl-Makarim Aboueissa, PhD*
*Professor, Statistics and Data Science*
*Graduate Coordinator*
*Department of Mathematics and Statistics*
*University of Southern Maine*
On Sat, Nov 13, 20
Hi Abou,
Perhaps this will be helpful. Be aware that you will cop some flak for
putting error bars on a bar plot.
aadat<-data.frame(group=c(rep("Exp",50),rep("Con",50)),
v1=sample(0:1,100,TRUE),
v2=sample(0:1,100,TRUE),
v3=sample(0:1,100,TRUE),
v4=sample(0:1,100,TRUE),
v5=sample(0:1,100,TRUE)
Dear All:
I do have a binary data set with multiple variables, event = 1 in all
variables. As an example, I attached a data set with 6 variables. The first
column is the grouping variable. Then the next 5 columns are the binary
data for 5 variables.
- Can we compute the confidence interval fo
On 4/26/20 11:26 AM, Alex Serafim wrote:
there is a function called "confbands", which is no longer available in
software R. It is not "confband" or "confBands", but "confbands", I need to
use this object to add confidence intervals in my work. Why is this
function not available?
attached is an
there is a function called "confbands", which is no longer available in
software R. It is not "confband" or "confBands", but "confbands", I need to
use this object to add confidence intervals in my work. Why is this
function not available?
attached is an image that shows how the graph should look,
Depending on the procedure used for estimating the CI, especially if the
default rankscore inversion method, then it is possible that legitimate end
points of the intervals for some quantiles with a given alpha (e.g., 0.05
for 95% CI) cannot be refined beyond plus or minus infinity. Of course,
thi
Hi all,
I am using the quantile regression package for estimating some models.
However, in some cases the intervals' upper bounds are either abnormally
high or low, with values such as -1.797693e+308 or 1.797693e+308. Actually,
the number is the same in absolute terms.
Does anyone know a reasonab
> On Mar 19, 2016, at 12:36 AM, Majid Javanmard
> wrote:
>
> Hello everyone
>
> here is the code that implements bagging using ipred package in R :
>
> library(ipred)
> library(mlbench)
> data("BostonHousing")
> # Test set error (nbagg=25, trees pruned): 3.41 (Breiman, 1996a, Table 8)
> mod <
Hello everyone
here is the code that implements bagging using ipred package in R :
library(ipred)
library(mlbench)
data("BostonHousing")
# Test set error (nbagg=25, trees pruned): 3.41 (Breiman, 1996a, Table 8)
mod <- bagging(medv ~ ., data=BostonHousing, coob=TRUE)
print(mod)
pred <- predict(mod
Hello everyone
here is the code that implements bagging using ipred package :
library(ipred)
library(mlbench)
data("BostonHousing")
# Test set error (nbagg=25, trees pruned): 3.41 (Breiman, 1996a, Table 8)
mod <- bagging(medv ~ ., data=BostonHousing, coob=TRUE)
print(mod)
pred <- predict(mod)
pre
TX 77840-4352
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of R Martinez
Sent: Tuesday, January 26, 2016 2:12 PM
To: r-help@r-project.org
Subject: [R] Confidence Interval for R-squared
To the list,
Does R have a function for computing the confidence
ment of Social and Health Services
> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of R Martinez
> Sent: Tuesday, January 26, 2016 12:12 PM
> To: r-help@r-project.org
> Subject: [R] Confidence Interval for R-squared
>
> To the list,
&g
Hi Raul,
Searching for "confidence interval of R-squared" on rseek.org turns up
some packages that might be of use, including bootstrap and MBESS.
On Tue, Jan 26, 2016 at 3:11 PM, R Martinez wrote:
> To the list,
>
> Does R have a function for computing the confidence interval of R-squared
>
To the list,
Does R have a function for computing the confidence interval of R-squared
(coefficient of determination)?
I checked R's Help function with “confidence interval” as the query but none of
the packages and functions that R found pertain to R-squared.
Thanks in advance for your help.
Hi all,
I am fitting a random slope and random intercept model usign lme
fucntion as shown below. Type is factor with two levels. I would like
to to find a confidence interval for mean of this model. Note that the
variance we use in finding the confidence interval should include the
variariance c
Hello,
When using wilcox_test from coin I got a sample estimator which does not lie
in the confidence interval.(see below) How is that possible? (The
documentation said that both referre to some kind of pseudo median but it
seems to be the same for both the confidence interval and the samplle
estim
Hi to
everyone, I have a big data set where rows are observations and columns are
variables. It contains a lot of missing values. I have used multiple imputation
with library mice and I get an exact prediction of each missing value. Now, I
would like to know the error I can commit or the confid
Hi,
I am using rpart with method="anova".Can we compute 95% confidence
intervals and prediction interval for the predicted mean at each node?
Thanks,
Puja
[[alternative HTML version deleted]]
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https://stat.
At 04:26 8/04/2013, you wrote:
Hello,
I have the following r-codes for solving a quasilikelihood estimating
equation:
>library(geepack)
>fit<-geese(y~x1+x2+x3,jack=TRUE,id=id,scale.fix=TRUE,data=dat,mean.link =
"logit", corstr="independence")
Now my question is how can I calculate the confiden
Hello,
I have the following r-codes for solving a quasilikelihood estimating
equation:
>library(geepack)
>fit<-geese(y~x1+x2+x3,jack=TRUE,id=id,scale.fix=TRUE,data=dat,mean.link =
"logit", corstr="independence")
Now my question is how can I calculate the confidence interval of the
parameters of
Hello,
I have the following r-codes for solving a quasilikelihood estimating
equation:
>library(geepack)
>fit<-geese(y~x1+x2+x3,jack=TRUE,scale.fix=TRUE,data=dat,mean.link =
"logit", corstr="independence")
Now my question is how can I calculate the confidence interval of the
parameters of the ab
The first thing you are missing is the documentation -- try ?survfit.object.
fit <- survfit(Surv(time,status)~1,data)
fit$std.err will contain the standard error of the cumulative hazard or
-log(survival)
The standard error of the survival curve is approximately S(t) * std(hazard), by the d
Have you found a solution for this? I am also trying to find a way to
retrieve the confidence intervals for the predictions.
Best regards,
João Oliveirinha
On Sunday, October 30, 2011 7:04:03 PM UTC, Muhammed Akbulut wrote:
>
> Hi,
>
> Is it possible to calculate confidence intervals for suppor
Hello,
How could we get the confidence interval when using the whittleFit
method from fArma package?
--
Thanks,
Barun Saha
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PLEASE do read the posting guide http://www.R-p
Assuming a distribution defined solely by those moments it is possible
(e.g., z- or t-test confidence intervals) but this isn't really the
place to discuss such things since there's no R content to your
question: try stats.stackexchange.com
Michael
On Wed, Jan 11, 2012 at 4:56 AM, lambdatau wrot
Hi all,
I'm wondering whether it is possible to construct a confidence interval
using only the mean, variance, skewness and kurtosis, i.e. without any of
the population?
If anyone could help with this it'd be much appreciated (even if just a
confirmation of it being impossible!).
Thanks.
--
Vie
Hi,
Is it possible to calculate confidence intervals for support vector
regression?
In the "ksvm{kernlab}" manual, it says that it supports confidence
intervals for regression.
However, i couldn't find any information about how to calculate confidence
interval.
Do you have any documents or example
Dear All,
Apologies if you have a seen a question like this from me before. I am hoping
that if I re-word my question more carefully someone may be able to offer more
help than the last time I asked something similar. I am using R 2.9.2 and
Windows XP.
I am trying to determine if there is a
Would someone tell me how they propose to go from "standard errors" to
confidence intervals*. I suspect Doug Bates would probably like to
know, also, as he has expended a lot of effort on this over the years,
I believe. :-)
-- Bert
* Note +/- 2 std errors is almost certainly not the right answ
Hi:
On Mon, Aug 8, 2011 at 10:07 AM, bjmjarrett wrote:
> Hi all,
>
> I’m trying to plot confidence intervals for the fitted values I get with my
> lme model in R.
Which fitted values? The ones conditional on the random effects or the
ones averaged over the random effects? The standard errors of
I don't know lme models very well, but if you have standard errors for your
values, this shouldn't be too hard (as a last resort) using polygon()
For example
x = 1:10
y = x^2
y.Err = 2*x
y.Up = y + y.Err; y.Dn =y-y.Err
# This graph is actually quite ugly so don't copy the formatting
plot(x,y
Hi all,
I’m trying to plot confidence intervals for the fitted values I get with my
lme model in R.
Is there any way I can plot this in the form of a shaded band, like the
output of geom_smooth() in ggplot2 package. ggplot2 seems to use only lm,
glm, gam, loess and rlm as smoothing methods.
Any
On 24/06/11 01:44, Adriana Bejarano wrote:
Dear R gurus,
I have the following code, but I still not know how to estimate and extract
confidence intervals (95%CI) from resampling.
Some sound advice --- still sound after all these years I believe --- in
respect
of boot strap confidence inter
boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of David Winsemius
> Sent: 23 June 2011 15:25
> To: Adriana Bejarano
> Cc: r-help@r-project.org
> Subject: Re: [R] Confidence interval from resampling
>
>
> On Jun 23, 2011, at 9:44 AM, Adriana Bejarano w
On Jun 23, 2011, at 9:44 AM, Adriana Bejarano wrote:
Dear R gurus,
I have the following code, but I still not know how to estimate and
extract
confidence intervals (95%CI) from resampling.
If you have a distribution of values, say "resamp.stat", of a
statistic from a properly performed
Dear R gurus,
I have the following code, but I still not know how to estimate and extract
confidence intervals (95%CI) from resampling.
Thanks!
~Adriana
#data
penta<-c(770,729,640,486,450,410,400,340,306,283,278,260,253,242,240,229,201,198,190,186,180,170,168,151,150,148,147,125,117,110,107,104
Hello-
I am looking for R function that will give me some proper confidence
intervals on un-transformed mean prediction when performing a linear
regression on log-transformed data. I am referring to the UMVU estimate, the
el-shaarawi and viveros (1997) estimate, or the Wu, wong, and Wei (2005)
est
On May 21, 2011, at 3:27 AM, Zablone Owiti wrote:
Dear Users,
I wish to know at what confidence level is the confidence interval
provided in the Spectrum function (plot.spec) plots.
The default level is clearly indicated in the arguments of the Usage
section on the help page of plot.spec
Dear Users,
I wish to know at what confidence level is the confidence interval
provided in the Spectrum function (plot.spec) plots.
The only information provided in the help regarding this is : a confidence
interval will be plotted by plot.spec: this is asymmetric, and the width of
the centre
Dear David,
Thank you for your reply. I have come across rcorrp.cens before. However,
I'm not sure it does quite what I want it to. It seems to compare whether
one predictor is more concordant than another within the same survival
function. I want to see whether one predictor is more concordan
On May 5, 2011, at 8:20 AM, Laura Bonnett wrote:
Dear All,
I am trying to calculate a 95% confidence interval for the
difference in two
c statistics (or equivalently D statistics). In Stata I gather that
this
can be done using the lincom command. Is there anything similar in R?
Have y
Dear All,
I am trying to calculate a 95% confidence interval for the difference in two
c statistics (or equivalently D statistics). In Stata I gather that this
can be done using the lincom command. Is there anything similar in R?
As you can see below I have two datasets (that are actually two i
Dear Steffi,
On Tue, Apr 5, 2011 at 7:26 AM, Stefanie Von Felten wrote:
> Dear Josh,
>
> Thanks for your help!
>
> Does your answer mean, that you agree the two methods should do the same,
> and what I was guessing, despite the small differences?
That would be my guess, but I have not actually r
Hi Stefanie,
Just to be clear, we are talking about differences in the third or
lower decimal place (at least with R version 2.13.0 alpha (2011-03-17
r54849), Epi_1.1.20). This strikes me as small enough that both
functions may be implementing the same method, but maybe slightly
different ways of
Hello,
Does anyone know which method from Newcombe (1998)* is implemented in prop.test
for comparing two proportions?
I would guess it is the method based on the Wilson score (for single
proportion), with and without continuity correction for prop.test(...,
correct=FALSE) and prop.test(..., co
--- begin included message ---
May I know how to obtain the confidence interval of the survival curve
of
weighted Cox regression model?
I tried coxph, cph, and coxphw, but they did not work.
Any help would be much appreciated.
end inclusion ---
Use the latest version of the survival pacakge
On Feb 15, 2011, at 9:05 PM, jeanneyue wrote:
Hi,
May I know how to obtain the confidence interval of the survival
curve of
weighted Cox regression model?
I tried coxph, cph, and coxphw, but they did not work.
Any help would be much appreciated.
One possible reason that this question may
Hi,
May I know how to obtain the confidence interval of the survival curve of
weighted Cox regression model?
I tried coxph, cph, and coxphw, but they did not work.
Any help would be much appreciated.
Thanks,
Jeanne
--
View this message in context:
http://r.789695.n4.nabble.com/Confidence-in
On 2011-02-13 18:31, Joshua Wiley wrote:
Hi,
The logical operators are actually vectorized, so I do not think you
need a loop. Does this do what you want?
## Some data
set.seed(10)
dat<- matrix(rnorm(500, sd = 3), nrow = 80)
## Hypothetical confidence interval
ci<- c(-5, 5)
## Find the numbe
Hi,
The logical operators are actually vectorized, so I do not think you
need a loop. Does this do what you want?
## Some data
set.seed(10)
dat <- matrix(rnorm(500, sd = 3), nrow = 80)
## Hypothetical confidence interval
ci <- c(-5, 5)
## Find the number of points outside interval
sum(dat < ci
Hi,
I am trying to determine how many points fall ouside the confidence interval
range.
This is the code I have so far but it does not work. Any help would be
appreciated.
Count <- vector ()
for (i in 1: nrow (dataname)){
if (dataname[i] u.ci.post[i]){
count[i] -> 1
}else
{count[i] -> 0}
}
sy
On 2011-2-6 22:56, Ben Bolker wrote:
Jinsong Zhao yeah.net> writes:
Hi there,
I have fitted a sample (with size 20) to a normal and/or logistic
distribution using fitdistr() in MASS or fitdist() in fitdistrplus
package. It's easy to get the parameter estimates. Now, I hope to report
the con
Jinsong Zhao yeah.net> writes:
>
> Hi there,
>
> I have fitted a sample (with size 20) to a normal and/or logistic
> distribution using fitdistr() in MASS or fitdist() in fitdistrplus
> package. It's easy to get the parameter estimates. Now, I hope to report
> the confidence interval for tho
Hi there,
I have fitted a sample (with size 20) to a normal and/or logistic
distribution using fitdistr() in MASS or fitdist() in fitdistrplus
package. It's easy to get the parameter estimates. Now, I hope to report
the confidence interval for those parameter estimates. However, I don't
find
On Jan 21, 2011, at 11:33 AM, Francesco Petrogalli wrote:
Hi,
I have a circular shaped set of point on the plane (X,Y) centered in
zero. The distribution is more dense close to zero and less dense far
from zero.
I need to find the radius of a circle centered in zero that contains
65% of the po
Hi,
I have a circular shaped set of point on the plane (X,Y) centered in
zero. The distribution is more dense close to zero and less dense far
from zero.
I need to find the radius of a circle centered in zero that contains
65% of the points in the sample. Is there any R directive that can do
this?
You need to add explicitly newdata = list(x=x) and if you want percentile
method you also
need se = "boot".
Roger Koenker
rkoen...@illinois.edu
On Jan 11, 2011, at 3:54 AM, Davey, Andrew wrote:
> I am using the quantreg package to build a quantile regression model and
> wish to generate conf
I am using the quantreg package to build a quantile regression model and
wish to generate confidence intervals for the fitted values.
After fitting the model, I have tried running predict() and
predict.rq(), but in each case I obtain a vector of the fitted values
only.
For example:
library(quant
dear M.,
I do not know how to get the SE for the joinpoint (or breakpoint) from
your ljr fit. However you can find useful the segmented package which
works for any GLM (including the logistic one) and it returns
(approximate) StErr (and Conf Int) also for the joinpoint (breakpoint in
the segme
I´m trying to run a logistic joinpoint regression utilising the ljr package.
I´ve been using the forward selection technique to get the number of knots for
the analysis, but I´m uncertain as to my results and the interpretation. The
documentation is rather brief ( in the package and the stats in
On Oct 30, 2010, at 11:33 AM, Brian Willis wrote:
HI,
I am using lmer() for a simple mixed effects model. The model is of
the form
logit(y)~ x + (1|z), where x is an indicator variable and z a multi-
level
factor.
I would like an estimate of the response variable (either y or logit
y)
Brian Willis manchester.ac.uk> writes:
> I am using lmer() for a simple mixed effects model. The model is of the form
> logit(y)~ x + (1|z), where x is an indicator variable and z a multi-level
> factor.
>
> I would like an estimate of the response variable (either y or logit y) with
> an associ
HI,
I am using lmer() for a simple mixed effects model. The model is of the form
logit(y)~ x + (1|z), where x is an indicator variable and z a multi-level
factor.
I would like an estimate of the response variable (either y or logit y) with
an associated confidence interval for a given value of x.
Hi,
How do I change Confidence Interval level (say from 95% to 80%) while
getting prediction intervals for ARMA mean models, and GARCH models in
R?
TIA
Aditya
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PLEASE do r
How do I calculate the confidence interval for the value x given by the
intersection of two quadratics (i.e. parabolas)?
I fit two quadratics of the form:
y = C1 + B1*x + A1*x^2
y = C2 + B2*x + A2*x^2
to two sets of points N1 and N2.
I test for whether they intersect, if they do then I cal
hello,
can someone tell me if there is a way to estimate a confidence interval for
a small non iid sample.
i computed a stratified boot.ci but i think it is not reasonable in the case
of such a small sample - are there any alternatives, can a conf.interval in
this case be estimated at all?
for
Hello all,
I am observing animals in a behavioural arena and recording their
distance from a specific point at regular time intervals (large enough
so that I can assume two successive positions are independent from
each other). Each animal provides a complete histogram of distances
which reflects
Hello,
I´ve got a statistical problem that I hope you can help me with. It doesn´t
have to do directly with R, so if there´s another forum which would suit
better, please tell me!
Now here´s the problem:
I want to derive confidence intervals for a variable X, which is - given the
descriptive
Dear List
>From a sample size of 40 I have calculated retrun level values for
>2,5,10,25,50 and 100 years using a exponentail disrtibution as follows;
Now how can I calculate confidence interval for
each return levels?
seeking your help. Thank you
Healthcare
greg.s...@imail.org
801.408.8111
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> project.org] On Behalf Of Devred, Emmanuel
> Sent: Wednesday, August 19, 2009 7:41 AM
> To: r-help@r-project.org
> Subject: [R] Conf
Regrading your second question, I guess somehow you get undefined value like
logarithm of zero of your target function for some unfortunate parameter
values in the parameter space.
Devred, Emmanuel wrote:
>
> Hi everyone,
>
> I have two questions:
>
> I would like to get confidence intervals
Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Devred, Emmanuel
Sent: Wednesday, August 19, 2009 9:41 AM
To: r-help@r-project.org
Subject: [R] Confidence interval on parameters from optim function
Hi everyone,
I have two questions:
9:41 AM
To: r-help@r-project.org
Subject: [R] Confidence interval on parameters from optim function
Hi everyone,
I have two questions:
I would like to get confidence intervals on the coefficients derived
from the optim() function.
I apply optim() to a given function f
> res <-
optim(c(0.08,0.04,1.
Hi everyone,
I have two questions:
I would like to get confidence intervals on the coefficients derived
from the optim() function.
I apply optim() to a given function f
> res <-
optim(c(0.08,0.04,1.),f,NULL,method="L-BFGS-B",lower=c(0.,0.,0.))
And I would like to get the p-value and confidence in
Thomas Seth Davis nau.edu> writes:
> I need help fitting/plotting a confidence interval to a frequency
distribution
>
In many medical journals, reviewers only want to see some error bars.
In 90% of the cases, these are wrong or misleading, but it is hopeless
to argue with medical professor
hi folks,
I need help fitting/plotting a confidence interval to a frequency
distribution
Can someone help with this?
thanks,
tsd
-Original Message-
> Date: Mon Apr 06 15:08:20 MST 2009
> From: r-help-requ...@r-project.org
> Subject: Welcome to the "R-help" mailing list
>
I wanted to send out a quick thanks to all that replied to my query about
estimating the confidence interval around the x-intercept of a linear
regression. The method I was able to implement in the most straightforward way
was taken from Section 3.2 of Draper and Smith (1998). Applied Regressio
(Ted Harding) wrote:
> On 24-Mar-09 03:31:32, Kevin J Emerson wrote:
...
> When I have time for it (not today) I'll see if I can implement
> this neatly in R. It's basically a question of solving
>
> (N-2)*(1 - R(X0))/R(X0) = qf(P,1,(N-1))
>
> for X0 (two solutions, maybe one, if any exist).
On Tue, Mar 24, 2009 at 5:25 AM, LiatL wrote:
> I've built a poisson regression model for multiple subjects by using the
> GLMER function. I've also developed some curves for defining its limits but
> I did not succeed in developing confidence interval for the model's curve
> (confint or predict
I've built a poisson regression model for multiple subjects by using the
GLMER function. I've also developed some curves for defining its limits but
I did not succeed in developing confidence interval for the model's curve
(confint or predict does not work - only for glm).
Does anyone know how can
On 24-Mar-09 03:31:32, Kevin J Emerson wrote:
> Hello all,
>
> This is something that I am sure has a really suave solution in R,
> but I can't quite figure out the best (or even a basic) way to do it.
>
> I have a simple linear regression that is fit with lm for which I
> would like to estimate
I should probably also add the health warning that the delta-method approach to
ratios of coefficients is REALLY BAD unless the denominator is well away from
zero.
When the denominator is near zero nothing really works (Fieller's method is
valid but only because 'valid' means less than you mi
On Mon, 23 Mar 2009, Kevin J Emerson wrote:
> Now, it is simple enough to calculate the x-intercept itself ( - intercept /
> slope ), but it is a whole separate process to generate the confidence
> interval of it. I can't figure out how to propagate the error of the slope
> and intercept into
Hello all,
This is something that I am sure has a really suave solution in R, but I can't
quite figure out the best (or even a basic) way to do it.
I have a simple linear regression that is fit with lm for which I would like to
estimate the x intercept with some measure of error around it (conf
Dear all,
I am looking for an R package that allows me to calculate and plot the
confidence limits for the roc curve using for example some bootstrapping.
I tried "ROCR" who seems doing such work but i couldn't find the right option
to do it.
Many thanks
Bests
Marc
___
rak1304 hotmail.com> writes:
> > > I am new to R and Im
some trouble with the following question...
I'm starting to study stats and R again after almost a year, so I
thought this is interesting. I think I have the answer. Here is how I
arrived at it:
> > Generate 100 standard normal N(0,1)
Yes it is a homework problem, I included the whole question as I thought it
would make it easier to explain however I am unsure of how to do the
confidence interval part. As far as I am aware I have set up a matrix with
my 100 samples of 100 and have calculated means. Do I need to set up a new
m
Rachel Keyes hotmail.com> writes:
>
>
> I am new to R and Im some trouble with the following question... Generate 100
standard normal N(0,1) samples
> of size 100, X1(k),...,X100(k) where k=1,...,100 (The k is and indicie in
brackets) Calculate the sample
> mean for each sample. For each sampl
I am new to R and Im some trouble with the following question... Generate 100
standard normal N(0,1) samples of size 100, X1(k),...,X100(k) where
k=1,...,100 (The k is and indicie in brackets) Calculate the sample mean for
each sample. For each sample mean Xbark the 0.95-confidence interval fo
I am new to R and Im some trouble with the following question...
Generate 100 standard normal N(0,1) samples of size 100, X1(k),...,X100(k)
where k=1,...,100 (The k is and indicie in brackets)
Calculate the sample mean for each sample.
For each sample mean Xbark the 0.95-confidence interval fo
On Sun, 2008-11-30 at 01:15 -0500, David Winsemius wrote:
> ?confint.glm # ... in MASS
That provides confidence intervals on the parameters of the model, which
is not what the OP wanted. He wants confidence intervals on:
predict(mod, newdat)
One way to do this is to compute them in the normal
?confint.glm # ... in MASS
On Nov 28, 2008, at 9:29 AM, Gerard M. Keogh wrote:
Hi all,
simple Q:
how do I extract the upper and lower CI for predicted probabilities
directly for a glm - I'm sure there's a one line to do it but I
can't find
it.
the predicted values I get with the predic
Hi all,
simple Q:
how do I extract the upper and lower CI for predicted probabilities
directly for a glm - I'm sure there's a one line to do it but I can't find
it.
the predicted values I get with the predict (.. "response")
Thanks
Gerard
*
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 tri
I am a new user of R package and I needed a help
regarding plotting confidence limits for FFT ( chisquare based) and
spectrum
using the monte carlo simulations of background red noise . How do I do
it
in R can any one help in this issue?
sudheer
--
Hi!
Here is a better code, using the percentil value instead the position, and
some corrections on the graph code.
The reason in the difference on the tails is elementar, but I don't had see
it before. The right and left limits are calculated by simulation, and his
differences from the mean are n
Thanks Professor and Bernardo,
What I'm trying to do is this: I have a macro for Minitab. His author says
it's a "Monte Carlo simulation to estimate a confidence interval". But and
don't have Minitab, don't like to work with illegal licenses, and LOVE R.
So, I re-write the macro in a R script.
Be
Em Ter, 2008-08-19 às 23:25 -0300, Raphael Saldanha escreveu:
> Hi!
>
> With the following script, I'm trying to make a demonstration of a
> Confidence Interval, but I'm observing some differences on tails.
Raphael,
If you make demonstration of Confidence Interval why you don't use
"ci.examp" of
On Tue, 19 Aug 2008, Raphael Saldanha wrote:
Hi!
With the following script, I'm trying to make a demonstration of a
Confidence Interval, but I'm observing some differences on tails.
You need to tell us what you are trying to do. You seem to be computing a
parametric bootstrap interval, but
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