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NZAMT NZQA NZ Grapher NZ Maths Census at School Study It

3.8 Time Series HOME | Achievement Objectives | Overview | The Statistics Cycle
NZ Grapher: The best choice | iNZight: Getting Started , Importing Data
Using EXCEL: Smoothing, Trend, Seasonal Effects, Graphing, Forecasts, Seasonal Adjustment, Non-Linear models, Comparing Excel & iNZight
Report Writing: Summary | Introduction | Trend | Decompose | Recompose | Seasonal Effect | Forecasts | Robustness | Additive vs Multiplicative model | Comparing | Combining | Conclusion | Practice Assessment

Model Robustness & Re-predicting values

8

 

Using iNZight to test Model Robustness

(Excellence)
The robustness of the iNZight modeling can be tested by removing some recent data, then predicting the data again using iNZight. The estimates can then be compared with the original (and the confidence intervals).

Did the modeling reproduce the data well, or not? Discuss

If the actual data values are within the 95% prediction interval for the estimates (predictions) then the model is robust.

 

Word Docs Class notespdf

Excel File German Visitors to NZ comparing excel with iNZight predictions (& the iNZight csv)

EXEMPLARS:
Use iNZight to produce a time series graph and add the trend line. Copy this into your report and discuss

- Alcohol Consumptn: Data csv,| Word Worksheet | Google Doc class write up

- Travel Destination Data csv | Word Write up | Google Doc class work

- Travel Purposes: Data csv

- Electricity Production: Data csv | (Website)

 

Comparing Actual Data to Re predicted Values

How?

 

Record the actual data values that you are intending to remove.

Then delete out some data values at the end of the time series.

How?

Filter data - Select cases,

Select Row number, proceed (and enter in row numbers)

You will need to check the row numbers before you start

Then proceed.

Redo the predictions (estimates) as normal

Compare the Estimates and the Actual data values (with considerations of the 95% prediction intervals)

Discuss this (in context)

 

 

ACTUAL

Aug

3949

Sept

4331

Oct

6446

ESTIMATE

 

The estimates (Aug 5100, Sept 5600, & Oct 7100 visitors) are all greater than the actual data (Aug 5100, Sept 5600, & Oct 7100 visitors from Germany)

Only the October actual data value (6446 visitors) was within the 95% prediction interval for the estimates (6070 to 8190 visitors). The values for August & September were both below the lower limit of the 95% prediction interval.

This indicates that the iNZight Holt-Winters LOWESS technique is not that robust in this situation. The removal of the last three data values caused the trend line to change to increase after 2012, thus producing higher estimates than the actual data, as can be seen in the graph below:

Example: Tourist numbers to NZ from Germany

Excel Predictions:

iNZight Predictions

 

 

iNZight fitted

lower 95% bound

upper 95% bound

Excel Prediction

Nov-12

10213

9292

11133

11001

Dec-12

12067

11044

13090

11791

Jan-13

13977

12860

15094

13084

Feb-13

14837

13633

16042

14301

Mar-13

12643

11357

13929

12887

Apr-13

8505

7141

9869

9063

May-13

5547

4108

6985

6810

Jun-13

4291

2781

5800

5820

Jul-13

4127

2549

5706

6051

Aug-13

4330

2685

5975

6158

Sep-13

5093

3384

6803

6407

Oct-13

7005

5233

8777

7805

Nov-13

10774

8770

12777

11395

Dec-13

12628

10569

14686

12185

Jan-14

14538

12426

16650

13478

Feb-14

15398

13233

17564

14695

Mar-14

13204

10987

15421

13281

 

 

 

 

(you tube video by Pricilla Allan)

 

 

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