On Tue, Nov 13, 2012 at 11:59 AM, Rolf Turner wrote:
>
> My apologies for returning to this issue after such a considerable
> length of time ... but I wanted to check the result in Cramer's book,
> and only yesterday managed to get myself organised to go the
> library and check it out.
>
> What b
My apologies for returning to this issue after such a considerable
length of time ... but I wanted to check the result in Cramer's book,
and only yesterday managed to get myself organised to go the
library and check it out.
What bothers me is what happens when f(Q.p) = 0. The formula
that you
[see in-line below]
On 31-Oct-2012 10:26:14 PIKAL Petr wrote:
> Hi Ted
>
>> -Original Message-
>> From: ted@deb [mailto:ted@deb] On Behalf Of Ted Harding
>> Sent: Tuesday, October 30, 2012 6:41 PM
>> To: r-help@r-project.org
>
>
>
>>
>> The general asymptotic result for the pth quanti
The rank test inversion option that you are trying to use won't
work with only one coefficient, and therefore with univariate
quantiles, if you use summary(rq(rnorm(50) ~ 1, tau = .9), cov = TRUE)
you will have better luck.
url:www.econ.uiuc.edu/~rogerRoger Koenker
emailrkoen.
t; Cc: r-help@r-project.org help
> Subject: Re: [R] standard error for quantile
>
> Petr,
>
> You can do:
>
> require(quantreg)
> summary(rq(x ~ 1, tau = c(.10,.50,.99))
>
>
> url:www.econ.uiuc.edu/~rogerRoger Koenker
> emailrkoen..
Hi Ted
> -Original Message-
> From: ted@deb [mailto:ted@deb] On Behalf Of Ted Harding
> Sent: Tuesday, October 30, 2012 6:41 PM
> To: r-help@r-project.org
>
> The general asymptotic result for the pth quantile (0 sample of size n is that it is asymptotically Normally distributed with
>
Hi Bert
> -Original Message-
> From: Bert Gunter [mailto:gunter.ber...@gene.com]
> Sent: Tuesday, October 30, 2012 3:37 PM
> To: PIKAL Petr
> Cc: r-help@r-project.org
> Subject: Re: [R] standard error for quantile
>
> Petr:
>
> 1. Not an R question.
Par
> -Original Message-
> From: Jim Lemon [mailto:j...@bitwrit.com.au]
> Sent: Wednesday, October 31, 2012 9:56 AM
> To: PIKAL Petr
> Cc: r-help@r-project.org
> Subject: Re: [R] standard error for quantile
>
> On 10/31/2012 12:46 AM, PIKAL Petr wrote:
> > Dear all
> >
&
On 10/31/2012 12:46 AM, PIKAL Petr wrote:
Dear all
I have a question about quantiles standard error, partly practical
partly theoretical. I know that
x<-rlnorm(10, log(200), log(2))
quantile(x, c(.10,.5,.99))
computes quantiles but I would like to know if there is any function to
find stan
On 30-Oct-2012 13:46:17 PIKAL Petr wrote:
> Dear all
>
> I have a question about quantiles standard error, partly practical
> partly theoretical. I know that
>
> x<-rlnorm(10, log(200), log(2))
> quantile(x, c(.10,.5,.99))
>
> computes quantiles but I would like to know if there is any funct
Petr,
You can do:
require(quantreg)
summary(rq(x ~ 1, tau = c(.10,.50,.99))
url:www.econ.uiuc.edu/~rogerRoger Koenker
emailrkoen...@uiuc.eduDepartment of Economics
vox: 217-333-4558University of Illinois
fax: 217-244-6678
Petr:
1. Not an R question.
2. You want the distribution of order statistics. Search on that. It's
basically binomial/beta.
-- Bert
On Tue, Oct 30, 2012 at 6:46 AM, PIKAL Petr wrote:
> Dear all
>
> I have a question about quantiles standard error, partly practical
> partly theoretical. I know
Dear all
I have a question about quantiles standard error, partly practical
partly theoretical. I know that
x<-rlnorm(10, log(200), log(2))
quantile(x, c(.10,.5,.99))
computes quantiles but I would like to know if there is any function to
find standard error (or any dispersion measure) of th
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