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> -Original Message-
> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
> project.org] On Behalf Of Gabor Grothendieck
> Sent: Wednesday, September 24, 2008 6:29 AM
> To: zhijie zhang
> Cc: [EMAIL PROTECTED]
> Subject: Re: [R] Generati
Check out JohnsonFit in SuppDists.
On Tue, Sep 23, 2008 at 10:59 AM, zhijie zhang <[EMAIL PROTECTED]> wrote:
> Dear R users,
> I hope to explain the concepts of skewness and kurtosis by generating
> series of distributions with same skewness and different kurtosis or with
> same kurtosis and dif
Well, let's take the Beta distribution for example. See
http://en.wikipedia.org/wiki/Beta_distribution for the formulae of
skewness and kurtosis. We can fix the skewness at, say, 2 and let
alpha = 1, then solve beta from the equation of "skewness = 2", you
will get beta =
1.8164966 or 0.1835034 app
Yihui,
Could you please show me an example?
What u have refered is clear for me, but i think the thing that i donot
know how to handle with is to link the relationships between
skewness/kurtosis and the distributions?
Thanks.
On Tue, Sep 23, 2008 at 11:48 PM, Yihui Xie <[EMAIL PROTECTED]> w
On Tue, Sep 23, 2008 at 9:59 AM, zhijie zhang <[EMAIL PROTECTED]> wrote:
> Dear R users,
> I hope to explain the concepts of skewness and kurtosis by generating
> series of distributions with same skewness and different kurtosis or with
> same kurtosis and different skewness, but it seems that i
Hi,
Certainly it's possible. Use any distribution function as long as you
can change its skewness and kurtosis, e.g. the Chi-square
distribution. The corresponding R functions are p*, q*, d*, and r* - I
think you know these functions already (e.g. rchisq()).
The only thing that you should be clea
Dear R users,
I hope to explain the concepts of skewness and kurtosis by generating
series of distributions with same skewness and different kurtosis or with
same kurtosis and different skewness, but it seems that i cannot find the
right functions.
I have searched the mailing list, but no answ
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