
10-09-2015
ets_kps
SAS Employee
Member since
07-23-2012
- 89 Posts
- 1 Likes Given
- 6 Solutions
- 49 Likes Received
-
Latest posts by ets_kps
Subject Views Posted 1683 09-25-2015 03:12 PM 1849 08-25-2015 04:51 PM 1849 08-25-2015 04:49 PM 9664 08-25-2015 03:37 PM 9720 08-24-2015 05:29 PM 2072 08-13-2015 11:56 AM 3218 08-13-2015 11:52 AM 3384 08-12-2015 10:54 AM 3384 08-11-2015 04:46 PM 3384 08-10-2015 01:58 PM -
Activity Feed for ets_kps
- Got a Like for Re: poisson regression using sas. 04-16-2020 04:13 PM
- Got a Like for Re: Proc Similarity to cluster time series data. 04-09-2017 10:27 PM
- Posted Re: Interval option in MARKETDATA (RiskDimension) on SAS Forecasting and Econometrics. 09-25-2015 03:12 PM
- Got a Like for Re: Help needed to model the impact of a long term promotional tactic on sales. 09-01-2015 04:24 AM
- Got a Like for Re: Proc Autoreg -- autoregressive parameters assumed given. 09-01-2015 04:24 AM
- Got a Like for Re: SAS/STAT procedure to calculate before and after performance analysis?. 09-01-2015 04:24 AM
- Got a Like for Re: Predicting the rank of a candidate on a party list - Help requested. 09-01-2015 04:24 AM
- Got a Like for Re: 2-stage regression with more than 2 models. 09-01-2015 04:24 AM
- Got a Like for Re: Logistic Regression with Instrumental Variable. 09-01-2015 04:24 AM
- Got a Like for Re: Estimating a Consumption-Based Asset Pricing Model. 09-01-2015 04:24 AM
- Got a Like for Re: Implying white's (1980) correction at proc panel procedure. 09-01-2015 04:24 AM
- Got a Like for Re: Selecting the Correct Forecasting/Prediction Proc (Feb-Dec year 1, Jan-Mar year 2). 09-01-2015 04:24 AM
- Got a Like for Re: proc varmax. 09-01-2015 04:24 AM
- Got a Like for Re: Proc ESM Seasonal Model Help. 09-01-2015 04:24 AM
- Got a Like for Re: Proc Panel and Parks. 09-01-2015 04:24 AM
- Posted Re: proc panel and heteroscedasticity correction on Statistical Procedures. 08-25-2015 04:51 PM
- Posted Re: proc panel and heteroscedasticity correction on Statistical Procedures. 08-25-2015 04:49 PM
- Posted Re: PROC IMPORT from Web on SAS Procedures. 08-25-2015 03:37 PM
- Posted PROC IMPORT from Web on SAS Procedures. 08-24-2015 05:29 PM
- Posted Re: 2-stage least squares regression on Statistical Procedures. 08-13-2015 11:56 AM
-
Posts I Liked
Subject Likes Author Latest Post 1 -
My Liked Posts
Subject Likes Posted 1 08-10-2015 01:58 PM 1 06-12-2014 11:33 AM 3 03-11-2013 11:18 AM 4 11-12-2012 10:01 AM 3 11-05-2013 04:25 PM -
My Library Contributions
Subject Likes Author Latest Post 0 1
11-20-2013
09:51 AM
I have a couple of suggestions. 1) Post the data and the example SAS file you are working on. (so we know where this is falling down) 2) Repost this in Forecasting and Econometrics as the "right" eyeballs are likely to see it over there. Best-Ken
... View more
11-20-2013
09:27 AM
This is likely because Jan is not in the model as it was dropped due to the "dummy variable trap." Make sure your tests refer to parameters that were actually estimated. -Ken
... View more
11-08-2013
03:30 PM
Did you come across these examples? Methods Matter: Improving causal Inference in Educational and Social Science Research
... View more
11-05-2013
04:25 PM
3 Likes
Hi Allie, In addition to Udo's request I thought i'd push you in a certain direction. The types of multiple seasonal/cycle models can be estimated in SAS using a UCM framework. You can think of this as ESM-like but with regressors. These regressors might be continous, such as a price, or dichotomous, such as a day. You might want to experiment a bit with the combination of seasonal length as well as some dummies for month to take care of those cycles. The dummy variable approach will require a good deal of data but as we don't know what you are working with, I'll just toss some ideas your way. SAS/ETS(R) 12.1 User's Guide Udo, might have more to add with some data. Regards-Ken
... View more
10-31-2013
10:40 AM
There are many directions to take your question but one technique you might want to consider is Stochastic Frontier Modeling. The underlying model assumes there is a maximum efficiency that can be obtained. Agents in the model can be evaluated based on their "closeness" to maximum efficiency. Here is a link to its implementation in SAS. SAS/ETS(R) 12.3 User's Guide Also, here a link to paper you might mind useful. http://isbm.smeal.psu.edu/library/working-paper-articles/2004-working-papers/06-2004-measuring-performance.pdf It doesn't sound as if your data are confidential. Would you like to share them?
... View more
10-28-2013
01:50 PM
Hello Amlan, Thank you for your question. Actually, I took your file and code and tried it on my 9.4 SAS with 12.3 SAS/ETS and the optimization completed just fine. My guess is that you are on a previous version of SAS/ETS. In recent years, the VARMAX routine has received algorithm improvements that greatly enhance optimization. If you are unable to upgrade to the newest version of SAS you might want to see if you can bump up the iterations and function calls, such as with nloptions maxiter=500 maxfunc=5000; Best of luck-Ken
... View more
10-25-2013
05:24 PM
1 Like
Hi Stephane, Yes, these output differences occur from time to time. Sorry it has been a trouble spot for you. To your second question, could you clarify? Are you looking to have SAS/ETS 12.1 documentation be the default home page? Rather than 9.x? thanks
... View more
09-27-2013
04:20 PM
here is a response from the developer: Given one data set containing two columns, exchangeRate and stockReturn (will need by groups for all countries in your example): Proc varmax data=one; Model exchangeRate stockReturn = / p=1; /* VAR(1) with constant mean */ Garch p=1 q=1 form=BEKK; /* BEKK GARCH(1,1) */ Run; Note that in proc varmax, we calculate constant term, C’C, in garch equation in equation (2) as one symmetric matrix. If the user wants to repeat the paper, he can apply Cholesky decomposition on the constant matrix (by using IML for example). I hope this helps. Also, please contact SAS tech support should you require additional help getting started with VARMAX.
... View more
09-12-2013
04:31 PM
Well, the first thing you need to do is reshape your data from WIDE to LONG with PROC TRANSPOSE. proc transpose data=wide out=long; by date; run; (the first post doesn't need this) Make sure your date variable is formatted as a date and then you can use the following code to accomplish the 12 month percentage change. It uses a new ETS procedure called TIMEDATA (h/t to the TIMEDATA developers for this). The other operations will be very similar. Just a little background on TIMEDATA... It is extremely efficient at the types of time series operations that you are trying to do. data verylarge; set sashelp.air; clientid=1; balances=air; run; proc timedata data=VERYLARGE out=_NULL_ outarray=trend plot=arrays; by clientid; id date interval=month accumulate=average; var balances; outarray trend; do t=1 to _LENGTH_; if t < _SEASONALITY_ then trend = .; else do; previous = balances[t-_SEASONALITY_]; recent = balances ; if previous = 0 then trend = .; else trend = (recent - previous) / previous; end; end; run;
... View more
08-19-2013
01:34 PM
Hi Mayank, Thanks for the question. Would you mind sharing some code for what you are doing? Perhaps a graph of the series or some background on the type of units? There are a number of simple examples at SAS/ETS(R) 12.1 User's Guide which could help to get you started. Thanks
... View more
07-19-2013
05:18 PM
Hi Niam, Thanks for the question. Yes, SAS has a number of procedures for nonlinear panel data models. I am going to TCOUNTREG: Count data models (Poisson and Negative Binomial) with Fixed and Random Effects (subject specific intercepts)SAS/ETS(R) 12.1 User's Guide NLMIXED: Syntax and models similar to PROC MIXED but non-linear models. SAS/STAT(R) 12.1 User's Guide You can also analyze repeated measures with GLIMMIX. I will warn you. Since you used the term "panel" and not "longitudinal" to describe the data, I am going to assume you are coming from more of an observational data background. For that reason some of the terminology of the *MIX*-type procedures may look a little odd at first glance. Let me know if you need any assistance getting started-Ken
... View more
04-11-2013
04:55 PM
In addition to Udo's reponse I would also ask what your particular objective is? If it is prediction, then perhaps not finding a huge response is acceptable. If, on the other hand, your objective is to find the marginal effect of the program then you might either re-examine the tool (PROC AUTOREG) or the functional form (lags: the effect might not be contemporaneous). My two cents.
... View more
04-11-2013
04:49 PM
Hi Jing, I spoke with the developer of proc model and he had this response, " For the SUR method MODEL computes a pseudo inverse of the OLS residuals’ covariance matrix. When the OLS covariance matrix is singular a warning is produced explaining which equations’ rows in the covariance matrix are linearly dependent, and PROC MODEL continues with the SUR estimation of parameters. If the user isn’t getting this warning message for a known deficient matrix then something else is going on " He also requested that he would be happy to look at your code and data if you wouldn't mind providing and example of the issue. - Ken
... View more
03-25-2013
02:45 PM
There is an alternative way to do this that doesn't involve using all this first., last. syntax. Using PROC TIMEDATA, you can directly reference the time series within BY groups. I feel the syntax is much more intuitive. Here is full sample in action. data greene; input firm year production cost @@; date = mdy(1,1,year); datalines; 1 1955 5.36598 1.14867 1 1960 6.03787 1.45185 1 1965 6.37673 1.52257 1 1970 6.93245 1.76627 2 1955 6.54535 1.35041 2 1960 6.69827 1.71109 2 1965 7.40245 2.09519 2 1970 7.82644 2.39480 3 1955 8.07153 2.94628 3 1960 8.47679 3.25967 3 1965 8.66923 3.47952 3 1970 9.13508 3.71795 4 1955 8.64259 3.56187 4 1960 8.93748 3.93400 4 1965 9.23073 4.11161 4 1970 9.52530 4.35523 5 1955 8.69951 3.50116 5 1960 9.01457 3.68998 5 1965 9.04594 3.76410 5 1970 9.21074 4.05573 6 1955 9.37552 4.29114 6 1960 9.65188 4.59356 6 1965 10.21163 4.93361 6 1970 10.34039 5.25520 ; proc sort data=greene out=greene; by firm year; run; proc timedata data=greene out=differenced; by firm; id date interval=year ; var cost /dif=(5); var production /diff=5; run; Yours might look like; PROC TIMEDATA data=returns out=returns2; by company; id Date interval=day; var price /diff=(1); run; There are also ways to do this in PROC PANEL
... View more
03-20-2013
10:28 AM
Just to add a bit to Udo's response.... There are full, runnable examples of UCM and SSM here. This example seems closest to your needs. Best of luck-Ken
... View more
- « Previous
- Next »