[R] how to generate a random data from a empirical distribition

[Frank Harrell]

Easiest thing is to sample with replacement from the original data. 
This is the idea behind the bootstrap, which is sampling from the 
empirical CDF.

Frank E Harrell Jr   Professor and Chairman        School of Medicine
                      Department of Biostatistics   Vanderbilt University

On Tue, 27 Jul 2010, Greg Snow wrote:

> Another option for fitting a smooth distribution to data (and generating future observations from the smooth distribution) is to use the logspline package.
>
> -- 
> Gregory (Greg) L. Snow Ph.D.
> Statistical Data Center
> Intermountain Healthcare
> greg.snow at imail.org
> 801.408.8111
>
>
>> -----Original Message-----
>> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
>> project.org] On Behalf Of xin wei
>> Sent: Monday, July 26, 2010 12:36 PM
>> To: r-help at r-project.org
>> Subject: [R] how to generate a random data from a empirical
>> distribition
>>
>>
>> hi, this is more a statistical question than a R question. but I do
>> want to
>> know how to implement this in R.
>> I have 10,000 data points. Is there any way to generate a empirical
>> probablity distribution from it (the problem is that I do not know what
>> exactly this distribution follows, normal, beta?). My ultimate goal is
>> to
>> generate addition 20,000 data point from this empirical distribution
>> created
>> from the existing 10,000 data points.
>> thank you all in advance.
>>
>>
>> --
>> View this message in context: http://r.789695.n4.nabble.com/how-to-
>> generate-a-random-data-from-a-empirical-distribition-
>> tp2302716p2302716.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
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