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1. Re: a gaussian with skewness and kurtosis? (score: 1): Author: "Jeffrey Wang" <jwang@insightful.com>; Date: Mon, 10 Jun 2002 10:03:47 -0700; The Gram-Charlier expansion (around a Gaussian density) can be used to obtain a distribution with arbitrary skewness and kurtosis. For a recent application in finance, please see: Jondeau, E., and Ro; /archives/html/s-news/2002-06/msg00077.html (8,586 bytes)
2. Re: a gaussian with skewness and kurtosis? (score: 1): Author: "Jeffrey Wang" <jwang@insightful.com>; Date: Mon, 10 Jun 2002 14:24:11 -0700; Thanks for the clarification. I misinterpreted the user's question: it seems that he really wants to generate random variables. But the referenced paper claims to have solved the negative density is; /archives/html/s-news/2002-06/msg00079.html (9,940 bytes)
3. Re: about aggregate (score: 1): Author: "Jeffrey Wang" <jwang@insightful.com>; Date: Thu, 20 Jun 2002 10:51:05 -0700; Here's the code to do it using aggregate(): [1] 12.918 Here's the code to do it using the generic roll() function in the new S+FinMetrics module: [1] 0.922 The second approach utilizes the colMeans(); /archives/html/s-news/2002-06/msg00179.html (8,442 bytes)
4. Re: Exchanging Indices of a Matrix (score: 1): Author: "Jeffrey Wang" <jwang@insightful.com>; Date: Tue, 25 Jun 2002 11:05:22 -0700; Use the aperm() function for transposing an array. =*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=*=* Jeffrey Wang Research Scientist Insightful Corp. (206) 802-2269 Is there an easy way to do the following; /archives/html/s-news/2002-06/msg00209.html (8,401 bytes)
5. Generate Truncated Normal Random Variate -- Original: Generating random real numbers (score: 1): Author: "Jeffrey Wang" <jwang@insightful.com>; Date: Wed, 4 Apr 2001 10:23:19 -0700; Univariate truncated normal random variates can be generated using so-called "integral transform theorem". For example, see the following references: Borsch-Supan and Hajivassiliou (1993): "Smooth Un; /archives/html/s-news/2001-04/msg00050.html (17,291 bytes)

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