Fw: (no subject)

classic Classic list List threaded Threaded
3 messages Options
Reply | Threaded
Open this post in threaded view
|

Fw: (no subject)

maram




Dear group,
Thank u so much 4 ur help. I've tried the link,
http://finzi.psych.upenn.edu/R/library/quantreg/html/akj.html

for adaptive kernel density estimation.
But since I'm an R beginer and the topic of adaptive estimation is new for me, i still can't figure out some of the arguments of
akj(x, z =, p =, h = -1, alpha = 0.5, kappa = 0.9, iker1 = 0)
I've a vector of 1000 values (my X), but I don't know how to get the Z and what's Kappa? I'm sorry if the question is trivial but I hope u could recommend some refrence if u know one.
Thank u so much again
Maram




________________________________
From: John Kane <[hidden email]>

Sent: Monday, June 29, 2009 10:35:49 PM
Subject: Re: [R] (no subject)


Perhaps?

http://finzi.psych.upenn.edu/R/library/quantreg/html/akj.html






> Subject: [R] (no subject)
> To: [hidden email]
> Received: Monday, June 29, 2009, 9:05 AM
> Hi group,
> I found a module for adaptive kernel density estimation for
> Stata users, but unfortunetly I don't have access to Stata,
> can I find a similar approach using R?
>
>
>      
>     [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email]
> mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained,
> reproducible code.
>

      __________________________________________________________________
Looking for the perfect gift? Give the gift of Flickr!




     
        [[alternative HTML version deleted]]


______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: Adaptive kernel density was ... Fw: (no subject)

David Winsemius

On Jul 12, 2009, at 3:21 PM, maram salem wrote:

>
> Dear group,
> Thank u so much 4 ur help. I've tried the link,
> http://finzi.psych.upenn.edu/R/library/quantreg/html/akj.html
>
> for adaptive kernel density estimation.
> But since I'm an R beginer and the topic of adaptive estimation is  
> new for me, i still can't figure out some of the arguments of
> akj(x, z =, p =, h = -1, alpha = 0.5, kappa = 0.9, iker1 = 0)
> I've a vector of 1000 values (my X), but I don't know how to get the Z

That does seem rather trivial. According to the help page, those are  
just the points at which the density should be estimated. The example  
in the help page shows you how to create a suitable vector.

> and what's Kappa?

Not so obvious. Experimentation shows that reducing kappa makes the  
estimates less smooth.

> I'm sorry if the question is trivial but I hope u could recommend  
> some refrence if u know one.

Koenker gives two references and apparently you have some other  
material you are reading. Your university should have access to the  
Project Euclid Annals of Statistics copies that are found with the  
obvious Google search strategy.  Maybe you should be questioning the  
overall strategy of using a function you don't understand. Why, for  
instance, do you even have an interest in this function?


> Thank u so much again
> Maram
> ________________________________
> From: John Kane <[hidden email]>
>
> Sent: Monday, June 29, 2009 10:35:49 PM
> Subject: Re: [R] (no subject)
>
>
> Perhaps?
>
> http://finzi.psych.upenn.edu/R/library/quantreg/html/akj.html
>
>
>> Subject: [R] (no subject)
>> To: [hidden email]
>> Received: Monday, June 29, 2009, 9:05 AM
>> Hi group,
>> I found a module for adaptive kernel density estimation for
>> Stata users, but unfortunetly I don't have access to Stata,
>> can I find a similar approach using R?
>>
>>

David Winsemius, MD
Heritage Laboratories
West Hartford, CT

______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: Adaptive kernel density was ... Fw: (no subject)

RKoenker

On Jul 12, 2009, at 2:56 PM, David Winsemius wrote:

>
> On Jul 12, 2009, at 3:21 PM, maram salem wrote:
>>
>> Dear group,
>> Thank u so much 4 ur help. I've tried the link,
>> http://finzi.psych.upenn.edu/R/library/quantreg/html/akj.html
>>
>> for adaptive kernel density estimation.
>> But since I'm an R beginer and the topic of adaptive estimation is  
>> new for me, i still can't figure out some of the arguments of
>> akj(x, z =, p =, h = -1, alpha = 0.5, kappa = 0.9, iker1 = 0)
>> I've a vector of 1000 values (my X), but I don't know how to get  
>> the Z
>
> That does seem rather trivial. According to the help page, those are  
> just the points at which the density should be estimated. The  
> example in the help page shows you how to create a suitable vector.
>
>> and what's Kappa?
>
> Not so obvious. Experimentation shows that reducing kappa makes the  
> estimates less smooth.
>
>> I'm sorry if the question is trivial but I hope u could recommend  
>> some refrence if u know one.
>
> Koenker gives two references and apparently you have some other  
> material you are reading. Your university should have access to the  
> Project Euclid Annals of Statistics copies that are found with the  
> obvious Google search strategy.  Maybe you should be questioning the  
> overall strategy of using a function you don't understand. Why, for  
> instance, do you even have an interest in this function?
>
The Silverman book on density estimation is as close to a canonical  
reference as one is
likely to encounter in statistics, the akj() function implements  
Silverman's adaptive kernel
proposal so it would be quite helpful to have this reference at hand.  
That is why it was
cited in the man page for the function.

______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.