turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

Find a Community

- Home
- /
- Analytics
- /
- Forecasting
- /
- Modelling ARIMA-ANN

Topic Options

- RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

Highlighted
# Modelling ARIMA-ANN

Options

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

10-26-2017 11:51 PM

Hello Pals;

Can anyone give me an idea of how to model auto regressive artificial neural network (ARIMA-ANN) in SAS UE, using the data below.

data WORK.WINE;

infile datalines dsd truncover;

input date:$8. y:32.;

datalines4;

Jan80,15136

Feb80,16733

Mar80,20016

Apr80,17708

May80,18019

Jun80,19227

Jul80,22893

Aug80,23739

Sep80,21133

Oct80,22591

Nov80,26786

Dec80,29740

Jan81,15028

Feb81,17977

Mar81,20008

Apr81,21354

May81,19498

Jun81,22125

Jul81,25817

Aug81,28779

Sep81,20960

Oct81,22254

Nov81,27392

Dec81,29945

Jan82,16933

Feb82,17892

Mar82,20533

Apr82,23569

May82,22417

Jun82,22084

Jul82,26580

Aug82,27454

Sep82,24081

Oct82,23451

Nov82,28991

Dec82,31386

Jan83,16896

Feb83,20045

Mar83,23471

Apr83,21747

May83,25621

Jun83,23859

Jul83,25500

Aug83,30998

Sep83,24475

Oct83,23145

Nov83,29701

Dec83,34365

Jan84,17556

Feb84,22077

Mar84,25702

Apr84,22214

May84,26886

Jun84,23191

Jul84,27831

Aug84,35406

Sep84,23195

Oct84,25110

Nov84,30009

Dec84,36242

Jan85,18450

Feb85,21845

Mar85,26488

Apr85,22394

May85,28057

Jun85,25451

Jul85,24872

Aug85,33424

Sep85,24052

Oct85,28449

Nov85,33533

Dec85,37351

Jan86,19969

Feb86,21701

Mar86,26249

Apr86,24493

May86,24603

Jun86,26485

Jul86,30723

Aug86,34569

Sep86,26689

Oct86,26157

Nov86,32064

Dec86,38870

Jan87,21337

Feb87,19419

Mar87,23166

Apr87,28286

May87,24570

Jun87,24001

Jul87,33151

Aug87,24878

Sep87,26804

Oct87,28967

Nov87,33311

Dec87,40226

Jan88,20504

Feb88,23060

Mar88,23562

Apr88,27562

May88,23940

Jun88,24584

Jul88,34303

Aug88,25517

Sep88,23494

Oct88,29095

Nov88,32903

Dec88,34379

Jan89,16991

Feb89,21109

Mar89,23740

Apr89,25552

May89,21752

Jun89,20294

Jul89,29009

Aug89,25500

Sep89,24166

Oct89,26960

Nov89,31222

Dec89,38641

Jan90,14672

Feb90,17543

Mar90,25453

Apr90,32683

May90,22449

Jun90,22316

Jul90,27595

Aug90,25451

Sep90,25421

Oct90,25288

Nov90,32568

Dec90,35110

Jan91,16052

Feb91,22146

Mar91,21198

Apr91,19543

May91,22084

Jun91,23816

Jul91,29961

Aug91,26773

Sep91,26635

Oct91,26972

Nov91,30207

Dec91,38687

Jan92,16974

Feb92,21697

Mar92,24179

Apr92,23757

May92,25013

Jun92,24019

Jul92,30345

Aug92,24488

Sep92,25156

Oct92,25650

Nov92,30923

Dec92,37240

Jan93,17466

Feb93,19463

Mar93,24352

Apr93,26805

May93,25236

Jun93,24735

Jul93,29356

Aug93,31234

Sep93,22724

Oct93,28496

Nov93,32857

Dec93,37198

Jan94,13652

Feb94,22784

Mar94,23565

Apr94,26323

May94,23779

Jun94,27549

Jul94,29660

Aug94,23356

;;;;

Accepted Solutions

Solution

11-17-2017
09:14 AM

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Chyke

10-31-2017 09:29 AM

There are several ways to model an "ANN" model.

1. Using neural net alone to model ANN(p,k) (i think it should be p, not q). You have to create p lags of the dependent variable as the input to the neural net with k hidden neurons. In addition, you can diff the data first and then modeling the diff instead of the original series so you are modeling something like ANN(p,d,k)

2. Stacking models. Take the residuals from the ANN model from 1 and modeling them using ARIMA(p,d,q). The final forecast will be the ANN forecast + ARIMA forecast

3. Ensemble models. Model ANN and ARIMA separately and take some sort of averaging (e.g. straight up average or regression based averaging) of the forecasts

4. Recurrent neural net. This model is much more complex and takes a lot of time to train. In practice methods 1 to 3 should be more than sufficient.

thanks

Alex

All Replies

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Chyke

10-27-2017 12:05 AM

Unfortunately that type of model is not supported within SAS UE

SAS UE does offer ARIMA but not neural networks, as far as I know.

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Reeza

10-27-2017 04:24 AM

Thanks,

but what suggestion can you give me. I am using it for my Thesis

but what suggestion can you give me. I am using it for my Thesis

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Chyke

10-27-2017 10:57 AM

Check if your University offers the full version of SAS - its usually available for a small cost, $99 at my University.

Or choose another software package such as Python or R.

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Chyke

10-27-2017 04:12 AM - edited 10-27-2017 04:14 AM

Hello Pals;

Can someone give me an idea of how to model an ARIMA(p,d,q)+ANN(q,k) 'autoregressive Neural network model in SAS UE, with the data below:-

data WORK.WINE; infile datalines dsd truncover; input date:$8. y:32.; datalines4; Jan80,15136 Feb80,16733 Mar80,20016 Apr80,17708 May80,18019 Jun80,19227 Jul80,22893 Aug80,23739 Sep80,21133 Oct80,22591 Nov80,26786

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Chyke

10-30-2017 03:43 PM

As mentioned above, neural networks are not supported in SAS University Edition. However, the general approach would be to model the data series with ARIMA for linear effects and then fit a neural network model to the residuals for non-linear effects.

You can use University Edition for the ARIMA model, but you will either have to get access to a different version of SAS that includes neural networks or use a different programming environment for the second part.

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to solarflare

11-17-2017 09:13 AM

Thank you

Solution

11-17-2017
09:14 AM

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Chyke

10-31-2017 09:29 AM

There are several ways to model an "ANN" model.

1. Using neural net alone to model ANN(p,k) (i think it should be p, not q). You have to create p lags of the dependent variable as the input to the neural net with k hidden neurons. In addition, you can diff the data first and then modeling the diff instead of the original series so you are modeling something like ANN(p,d,k)

2. Stacking models. Take the residuals from the ANN model from 1 and modeling them using ARIMA(p,d,q). The final forecast will be the ANN forecast + ARIMA forecast

3. Ensemble models. Model ANN and ARIMA separately and take some sort of averaging (e.g. straight up average or regression based averaging) of the forecasts

4. Recurrent neural net. This model is much more complex and takes a lot of time to train. In practice methods 1 to 3 should be more than sufficient.

thanks

Alex

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to Chyke

11-30-2017 10:34 AM

You can solve it by using Time Delay Neural Networks using PROC NEURAL. You have to create a skip layer perceptron architecture, having input nodes connected to hidden nodes and connected direct to the output node.