You have a conceptual problem, as pointed out by previous helpers.
You don't have a standard error for the first level of your categorical
variable because that level's effect is not estimated.
It is being used as a reference level against which the other levels of that
categorical variable are b
On Mar 13, 2012, at 9:38 AM, D_Tomas wrote:
Dear userRs,
when applied the summary function to a glm fit (e.g Poisson) the
parameter
table provides the categorical variables assuming that the first level
estimate (in alphabetical order) is 0.
Not really. It returns an estimate for the cont
Hi,
See inline.
On Tue, Mar 13, 2012 at 6:38 AM, D_Tomas wrote:
> Dear userRs,
>
> when applied the summary function to a glm fit (e.g Poisson) the parameter
> table provides the categorical variables assuming that the first level
> estimate (in alphabetical order) is 0.
>
> What is the standard
Mike,
Isn't this just an example of the wrong model giving a spurious
impression of precision? or more accurately, precision at the expense of
accuracy?
Here's a linear model example of the same thing...
set.seed(1)
n <- 400
x <- runif(n)-.5
y <- 2+ x*.2+ x^2 + rnorm(n)*.5
m1 <- lm(y~1)
m2 <- l
Hi Walter,
The paper can be found at
http://cran.r-project.org/web/packages/vars/vignettes/vars.pdf It seems
that you need the "vars" library before trying the function you mention.
What happens if you do the following?
install.packages("vars")
require(vars)
?cajorls
?ca.jo
HTH,
Jorge
On Wed
On Jan 8, 2010, at 6:45 AM, jjh wrote:
Hello-
Is it possible to estimate standard errors for a multiple regression
model
using a randomization test approach? I have seen a lot on using the
procedure to get a test statistic, but nothing that talks about
getting
actual standard errors. Is
Standard errors for the coefficients. Thanks!
Tal Galili wrote:
>
> Hi jjh,
> I wasn't able to understand: for what statistic do you want the standard
> error for? (The coefficients, the R^2 ?)
>
> Tal
>
>
> Contact
> Details:--
Hi jjh,
I wasn't able to understand: for what statistic do you want the standard
error for? (The coefficients, the R^2 ?)
Tal
Contact
Details:---
Contact me: tal.gal...@gmail.com | 972-52-7275845
Read me: www.talgalili.com (Heb
Peter Dalgaard wrote:
>
> alexander russell wrote:
>> Hello,
>> Mle2 is a little unforthcoming in the matter of standard errors? Is there
>> a
>> way to ask the program to supply standard errors along with estimates in
>> cases when it doesn't print them 'voluntarily'?
>> regards,
>> s
>
> Wha
alexander russell wrote:
> Hello,
> Mle2 is a little unforthcoming in the matter of standard errors? Is there a
> way to ask the program to supply standard errors along with estimates in
> cases when it doesn't print them 'voluntarily'?
> regards,
> s
What did you do? Which "cases"? Did you look a
Dear Bruno,
See the effects package (on CRAN) for a generalization of adjusted means.
I hope this helps,
John
--
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
web: socserv.mcmaster.ca/jfox
> -Original Message-
> Fr
Hi Bruno,
Apropos of "ls-means" ...
>> I have tried help.search and RSiteSearch with several terms including
>> "standard errors", "least square means", "adjusted means".
And "ls-means," which is what "you" call them?
There are many threads on this, spanning many years. The following,
RSiteSe
nts(st$conc,predict(puro1),pch=2,col="red")
> #
> isn't that what we want graphically and t(qq) gives us the values
> obviously quantile can be used with any set of p's
> [EMAIL PROTECTED]
>
>
> -Original Message-
> From: [EMAIL PROTECTED] on behalf of Ben
nd t(qq) gives us the values
obviously quantile can be used with any set of p's
[EMAIL PROTECTED]
-Original Message-
From: [EMAIL PROTECTED] on behalf of Ben Bolker
Sent: Tue 11/11/2008 3:09 PM
To: [EMAIL PROTECTED]
Cc: r-help@r-project.org
Subject: Re: [R] standard errors for predict.nls
Here's how far I've gotten. It's a start, but
I can't so far find a way to extract the actual
thing we want -- the bootstrap confidence intervals
on the predictions.
I apologize for not taking the time to go
read up on the boot library etc. etc. (I *have*
RTFM, but I haven't backtracked to th
On 7/11/2008, at 11:33 PM, Christoph Scherber wrote:
Dear all,
I would like to get standard errors (or confidence intervals) for
*predicted* values from an nls fit.
I have tried to implement code from p.225 in MASS (bootstrapping a
nls fit), but this gives only the
confidence intervals o
Dear all,
I would like to get standard errors (or confidence intervals) for *predicted*
values from an nls fit.
I have tried to implement code from p.225 in MASS (bootstrapping a nls fit), but this gives only the
confidence intervals of the parameter estimates, but not an overall confidence in
Dear Prof Ripley,
Am I correct if I use the following code to get c.i.´s for predicted values of
the nls fit:
puro1<-nls(rate~a*conc/(b+conc), data=Puromycin[1:12,], start=list(a=200, b=1))
#set up nls model
# assume only one predicted value is obtained using
predict(puro1,list(conc=0.02)):
On Mon, 3 Nov 2008, Ben Bolker wrote:
Prof Brian Ripley wrote:
Christoph Scherber agr.uni-goettingen.de>
writes:
Dear all,
Is there a way to retrieve standard errors from nls models?
The help page tells me that arguments
such as se.fit are ignored...
Many thanks and best wishes
Christoph
Prof Brian Ripley wrote:
>> Christoph Scherber agr.uni-goettingen.de>
>> writes:
>>
>>>
>>> Dear all,
>>>
>>> Is there a way to retrieve standard errors from nls models?
>>> The help page tells me that arguments
>>> such as se.fit are ignored...
>>>
>>> Many thanks and best wishes
>>> Christoph
>
On Mon, 3 Nov 2008, Ben Bolker wrote:
Christoph Scherber agr.uni-goettingen.de> writes:
Dear all,
Is there a way to retrieve standard errors from nls models?
The help page tells me that arguments
such as se.fit are ignored...
Many thanks and best wishes
Christoph
I have written some rea
Dear Christoph,
using the package 'alr3' it's not difficult!
Have a look at the following example:
## Fitting a Michaelis-Menten model
Puromycin.m1<-nls(rate~a*conc/(b+conc), data=Puromycin[1:12,],
start=list(a=200, b=1))
library(alr3)
## Predictions (with standard errors) at concentrations 0
Christoph Scherber agr.uni-goettingen.de> writes:
>
> Dear all,
>
> Is there a way to retrieve standard errors from nls models?
> The help page tells me that arguments
> such as se.fit are ignored...
>
> Many thanks and best wishes
> Christoph
I have written some reasonably generic
delta-
vcov(my_fit) should get you the whole variance matrix, so
sqrt(diag(vcov(my_fit))) should get you ONLY the standard errors.
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of threshold
Sent: Thursday, 28 February 2008 9:06 PM
To: r-help@r-project.org
Subject
threshold wrote:
> Hi, guess my problem has simple solution.
> I want to extract ONLY Std. Errors of Max. Lik. estimates
> (my_fit<-mle(object,...)), the same as I can do with estimates by:
> x<-as. matrix(coef(my_fit)).
> I could not find any function similar to 'coef(my_fit)', which extracts onl
Try this:
coef(summary(fit))[,2]
On 28/02/2008, threshold <[EMAIL PROTECTED]> wrote:
>
> Hi, guess my problem has simple solution.
> I want to extract ONLY Std. Errors of Max. Lik. estimates
> (my_fit<-mle(object,...)), the same as I can do with estimates by:
> x<-as. matrix(coef(my_fit)).
>
On Thu, 28 Feb 2008, threshold wrote:
> Hi, guess my problem has simple solution.
> I want to extract ONLY Std. Errors of Max. Lik. estimates
> (my_fit<-mle(object,...)), the same as I can do with estimates by:
> x<-as. matrix(coef(my_fit)).
> I could not find any function similar to 'coef(my_fit)
stderr_int <- summary(lm(y ~ x))$coefficients[1,2]
stderr_slope <- summary(lm(y ~ x))$coefficients[2,2]
Jeff.
On Oct 3, 2007, at 3:01 AM, Alexander Moreno wrote:
> Hi,
>
> If I have two vectors x and y and I do lm(y~x) and now I want to
> define
> variables that are the standard errors of the
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