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15 Jun 2009	Bloomberg Field Search A graphical Bloomberg Datafeed field searching utility Author: Ameya Deoras
13 Jan 2009	Winsorize data (using PRCTILE) Author: Dimitri Shvorob	Thank you! Very helpful. If it can do winsorize by group that would be better!

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23 Apr 2007		Winsorize data (using PRCTILE) Author: Dimitri Shvorob	winsorize, data, probability, statistics, nan, percentiles	139	2	4.5 4.5 \| 2 ratings

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File	MS_Regress - A Package for Markov Regime Switching Models in Matlab

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27 Oct 2009	MS_Regress - A Package for Markov Regime Switching Models in Matlab Functions to Estimate, Simulate and Forecast a markov switching model in Matlab Author: Marcelo Perlin	markov switching, statistics, modeling, regression, analysis, optimization	467	22	4.07692 4.1 \| 14 ratings
09 May 2005	Automatic Spectral Analysis Automatic spectral analysis for irregular sampling/missing data, analysis of spectral subband. Author: Stijn de Waele	arma, ma, ar, spectral analysis, vector ar, autocorrelation	68	6	4.5 4.5 \| 8 ratings

Comments and Ratings Matching Xing's Watch List			1-5 of 36
Date	File	Comment by	Comments	Rating
19 Sep 2009	MS_Regress - A Package for Markov Regime Switching Models in Matlab Functions to Estimate, Simulate and Forecast a markov switching model in Matlab	MehdiHK Hosseinkouchack	Dear Marcelo, I would like thank myself from your side for finding a little bug in your code. It is, however, excellent! I appreciate your efforts. Best of Wishes MehdiHK	Comment only
09 Aug 2009	MS_Regress - A Package for Markov Regime Switching Models in Matlab Functions to Estimate, Simulate and Forecast a markov switching model in Matlab	MehdiHK Hosseinkouchack	Dear Marcelo, This still does not solve the problem. I had a check on the probabilities: for k=2 I was checking if sum of the elements of the transition matrix adds up to 2, and it was not! well transposed or not transposed, rows or columns, does not matter now ... For comment B decreasing search space based on my comment is agreed then. Best of Wishes MehdiHK	Comment only
08 Aug 2009	MS_Regress - A Package for Markov Regime Switching Models in Matlab Functions to Estimate, Simulate and Forecast a markov switching model in Matlab	Marcelo Perlin	MehdiHK, For A), from what you wrote it seems that the the transition matrix in the reference you used has a different notation than mine. In short, my transposed transition matrix will be equal to yours. Therefore, for my code, you should be looking at columns for the full process in each state (and not rows). For B), I was not clear. I meant the decrease of one element in each state. So we agree. Regards.	Comment only
07 Aug 2009	MS_Regress - A Package for Markov Regime Switching Models in Matlab Functions to Estimate, Simulate and Forecast a markov switching model in Matlab	MehdiHK Hosseinkouchack	Dear Marcelo, A) I am pretty sure that the probabilities do not sum up to the correct value. As a check: for a k=2 case, try to check if sum of all the elements in Coeff.p always is equal to 1 in all the cases! B) About the search space, for a case of k=2, not that ONE parameters are more than enough, but that TWO are more than enough b/c P=[p11 p12; p21 p22] is identified if from each ROW exactly ONE element is know so 2 element is enough not 3. (you mentioned that 4 can be decreased by 1!!!) C) ROWS should sum up to ONE not columns. I closely looked into all of your codes. They are neat, but you have some mistakes that should be fixed. Thanks a lot Mehdi	Comment only
07 Aug 2009	MS_Regress - A Package for Markov Regime Switching Models in Matlab Functions to Estimate, Simulate and Forecast a markov switching model in Matlab	Marcelo Perlin	Dear MehdiHK, regarding your first comment, the way I coded the optimization problem was jsut a matter of simplicity in the algorithm. I'm fully aware that the search space could be decreased by one elemente by conducting it as a inequality optimization problem, as opposed to an equality one. For your second comments, the p values of the coefficients are fine and so is the way I coded the transition matrix. If you look closelly in MS_Regress_Fit, you'll see that I'm using constrained estimation so that the each column of Coeff.p is summing to 1, according to my choice of numerical convergence. If you have any further question, feel free to drop me an email. Marcelo.	Comment only

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