I am first time SAS forcast studio user, and wondering if anyone in the community can help me understand how to transfer the parameter eatimation of a model to a math expression( the actuall formula).
Here is the estimation I got from SAS:
Component | Parameter | Estimate | Standard Error | t Value | Approx Pr > |t| |
CS | MA1_1 | 0.32743 | 0.06042 | 5.42 | <.0001 |
CS | MA1_2 | 0.08164 | 0.06408 | 1.27 | 0.2038 |
CS | MA1_3 | 0.28965 | 0.0608 | 4.76 | <.0001 |
JP | SCALE | 0.71904 | 0.01027 | 69.98 | <.0001 |
JP | DEN1_1 | 0.03581 | 0.01478 | 2.42 | 0.0161 |
JP | DEN1_2 | 0.03784 | 0.01463 | 2.59 | 0.0103 |
CS is my dependent variable and JP is my independent variable.
Thanks!
As a minimum to come close to answering this question we would basically need the code used to generate your estimates as the answer depends on which procedure, the model statement and any options.
Hi Ballardw
Thanks for the reply. It is an ARIMA model.
here is the SAS code.
Proc HPFARIMASPEC
* Model: SUBSETARIMA
* Label: CS = D=(1) Q=( 1 2 3 ) NOINT + JP : D=(1) DEN=( 1 2 )
*/
MODELREPOSITORY = work.temp
SPECNAME=LEAF_1
SPECLABEL="ARIMA: CS ~ D = (1) Q = 3 NOINT + INPUT: Dif(1) JP DEN = 2"
SPECTYPE=SUBSETARIMA
SPECSOURCE=FSUI
;
FORECAST SYMBOL = CS TRANSFORM = NONE
NOINT
DIF = ( 1 )
Q = ( 1 2 3 ) ;
INPUT SYMBOL = JP
TRANSFORM = NONE
DIF = ( 1 )
DEN = ( 1 2 );
ESTIMATE
METHOD=CLS
CONVERGE=0.0010
MAXITER=50
DELTA=0.0010
SINGULAR=1.0E-7 ;
run;
Hello Tony,
I am not sure what you mean by an expression (or a math formula). The estimated model is an ARIMA transfer function model. These models are discussed in many time series analysis books, e.g. a book by Box and Jenkins, also see the ARIMA doc (and its references): SAS/ETS(R) 13.2 User's Guide
In any event, the specified model can be described as follows:
Let JP1 denote the first difference of JP, e_t denote the error at time t, and B denote the backward shift operator. The model is:
CS_t = CS_(t-1) + [ 0.71904 /(1 - 0.03581B - 0.03784B^2)] JP1_t + e_t - 0.32743 e_(t-1) - 0.08164 e_(t-2) - 0.28965 e_(t-2)
This is not a formula for computing the forecasts of CS. It is just a description of the model with estimated parameters.
Rajesh
Hi rselukar,
This is excatly what I need! Thanks!
Is it possible for me to set a formula for my independent varaibale (JP in this case)? So basically telling SAS what is the probability of JP going to each different value base on its probability distribution. Eg, if JP is 1000, then 20% it will be 500, and 80% it will be 2000 in next time point. And ask SAS forcast studio to run the simulation to predict the outcome in a certain period?
It is possible. You are describing a what-if analysis. In order to do this you must create a score function based on this model. See the SCORE statement documentation and example in the HPFENGINE procedure.
Hello -
Alternatively you should be able to use the scenario analysis feature in SAS Forecast Studio.
Thanks,
Udo
Hi Udo,
Can you give me some details of how to do it in scenario analysis? From what I know, I can manully put in some value for my independent variable, and SAS will produce the new predicted value base on the input. However, it is different in my case.
I know how much,and what is the probability JP_t will go up or down if I know the CS_t-1. The probability of JP going upward or downward is actually base on the previous CS value, if CS is big, then the probability of JP going downward increase, and vice versa. I have the probabilty formula for JP already.
Ultimately, I want to run a simulation to predict how many time my JP will go up or down in a certain period in the future.
Is it that possible in scenatio analysis?
Thanks
Hello -
This is not possible using SAS Forecast Studio currently.
Thanks,
Udo
Hi Udo,
Is there any other SAS software can do that?
We have base, enterprise guide, miner, and forecast studio so far.
Thanks
Hi rselukar,
I am wondering do you have a link or can you tell me where I can find the documentation for the SCORE statement you mentioned?
Thanks
See Chapter 22 "Using Forecasting Model Score Files and DATA Step Functions" of the SAS® Forecast Server Procedures User’s Guide
Thanks! Will check it out
Registration is now open for SAS Innovate 2025 , our biggest and most exciting global event of the year! Join us in Orlando, FL, May 6-9.
Sign up by Dec. 31 to get the 2024 rate of just $495.
Register now!
Learn how to run multiple linear regression models with and without interactions, presented by SAS user Alex Chaplin.
Find more tutorials on the SAS Users YouTube channel.