楼主: lightyang
4525 11

请问什么软件能做Markov chain的运算? [推广有奖]

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楼主
lightyang 发表于 2006-2-27 11:06:00 |AI写论文

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我知道有高斯,出了这个之外,还有什么软件能做?

谢谢!

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关键词:Markov Chain Mark Mar 软件 运算 Chain Markov

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manchengfu 发表于3楼  查看完整内容

lingo也可以吧.

StatFan 发表于2楼  查看完整内容

WinBUGS

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沙发
StatFan 发表于 2006-2-27 22:02:00
WinBUGS

藤椅
manchengfu 发表于 2006-2-27 23:05:00
lingo也可以吧.
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板凳
zhaosweden 发表于 2006-2-28 04:04:00
any programmable softwares, matlab, c (++), fortran, ...

报纸
lightyang 发表于 2006-2-28 09:42:00

感谢各位的建议。

但是还想知道如果用matlab, c (++), fortran等都需要自己编写程序吧

Winbugs是不是可以不能自己编写程序呢,哪里能下载到这个软件呢?

地板
StatFan 发表于 2006-2-28 22:05:00

7
woodhaven 发表于 2006-3-1 01:44:00
S-Plus can also do this.

8
zhaosweden 发表于 2006-3-1 06:08:00
do not rely on canned packages too much if you really want to econometrics.

9
lightyang 发表于 2006-3-3 19:37:00

谢谢大家的建议,

已经有些眉目了。

10
haoqm 发表于 2006-3-3 21:20:00

/* ==========================================================================================================================*/
/* MSVARlib Version 2.0 - December 2004 */
/* First Version - May 2004 */
/* Benoit BELLONE */
/* Copyright (C) 2004 by Benoit BELLONE. All rights reserved - http://bellone.ensae.net - e-mail: benoit.bellone@ensae.org */
/* To install and adapt this program : MSVARlib_readme.txt */
/* See for more detail : "Classical estimation of Multivariate Markov Switching Model with MSBVARlib " */
/*===========================================================================================================================*/

This version has been deeply enhanced .It introduces a general Multivariate Markov-Switching Regression framework and enables estimates dealing
with 5 different family models :

1, MS-Mean-Variance model : y[t,.]= 1.Beta_S(t)+ u(t) =mu(S(t)) +u(t)

2, MS-VAR(_p) - General model : y(t)=[1 yt-1,..yt-p]*Beta_S(t) +u(t) =x(t).Beta(S(t))+ u(t)


3, MS-VAR(_p) - Switch Intercept model : y(t)= mu(S(t)) + [ yt-1,..yt-p]*Delta(t) +u(t) = 1.*Beta_S(t)+z(t).Delta(t)+ u(t)

4, MS-OLS Mix model : y(t)=x(t)*Beta_S(t) +z(t)*Delta+u(t),

5, MS-OLS General model : y(t)=x(t)*Beta_S(t) +u(t) ,

notice that intercept is included in X(t) see setsample.prg for modifications

I also allows a full description of Covariance regime dependent (resp. independent) Matrices with tree options :
Heteroskedastic variance 1, Homoskedastic variance 2 , Full variance 3.

Automatic or manual parameters initialization are possible. A_priori initialiazing datations can be loaded if needed.

To a complete description of the programs, related tutorials and example programs, the reader should
refer to the attached article : 'Classical estimation of Multivariate Markov Switching Model with MSBVARlib "

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