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Demetra+ Quick Tour Versatile software. Choose the right tool Demetra+ main feature: multi-processing Demetra+ in production. Understanding.

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Presentation on theme: "Demetra+ Quick Tour Versatile software. Choose the right tool Demetra+ main feature: multi-processing Demetra+ in production. Understanding."— Presentation transcript:

1 Demetra+ jean.palate@nbb.be

2 Quick Tour Versatile software. Choose the right tool Demetra+ main feature: multi-processing Demetra+ in production. Understanding the re-estimation procedure The file system of Demetra+. Batch processing by means of WSACruncher Automation

3 1. Choose the right tool TaskToolsComments Interactive analysis (experts) Demetra+Single documents Black-box SAExcel add-insFor unskilled people. Not suited for repeating work Production Small sets (< 100) Demetra+ Excel add-in Excel add-in = light Demetra+ plugged in Excel Production Large sets Demetra+ (<1000) WSACruncher Demetra+ for interactive improvements, WSACruncher for bulk processing Production. Advanced (specific handling) Programming toolsSee special topic

4 2. Demetra+: using multi- processing Choose a default specification RSA4 or RSA5(c): automated procedure Exception (  pre-definition of the specification) – Specific calendar (National holidays...) – Specific needs (no outliers detection...) Create a new multi-processing Use the local menu in the Workspace Window (Multi- processing) Rename the multi-processing, if need be

5 Select the series Use drag-drop Consider the list container (Tools  Containers  List) to make easier selections [Repeat the selection procedure] Possibility to mix the specifications Possibility to mix the sources Run the processing Inspect the results The summary and the matrix view give useful general information (see especially the signs of trading days, leap year, Easter coefficients, the numbers of outliers).

6 Sort the results following the quality – Quality indicator = just an indicator (to be improved)!! – Inspect bad series firstly, but don't forget the other series – Use the priority field to mark important series (  sort by priority) Inspect and modify bad series – Problems in diagnostics: Spectral td peaks  calendar variables (remove pre- tests, modify options) Residuals – Skewness: log/level – Kurtosis: (difficult) critical value for outliers detection

7 Spectral seasonal peaks. Difficult – Seats:  Arima specification (use auto-modelling or Airline; try (2 1 0)(0 1 1)...). Box-Jenkins could be inappropriate. – X11:  filters Residual seasonality  Series span (shorter) or – Seats: Arima specification – X11:  filters – Other important outputs (personal preferences) Charts (main chart, SI-ratio) Arima spectrum (→ simplify if possible) Regression model (→ checks the significance / the signs of the coefficients, consider the number of outliers) Last residuals... Improve by trial and error (see above)

8 Generating the output – Users should prefer csv files More efficient, many outputs csv format depends on international settings (Windows)! Immediate (or easy) import in numerous software (or DB) – Usual options (default folders, presentation...) can be saved (see "Tools → Options → Outputs") – Feedback in the log window (location of the output...)

9 3. Understanding the re-estimation Classification of the parameters of a SA processing – Reg-Arima modelling Defining the "domain" of the model – Log/level – Type, time span of outliers – Regression variables (calendars...) – Arima model Defining the "selection procedure" – Fct, VA, diffAIC... Operational – TOL, maxiter – Decomposition – Diagnostics, output (not used in Demetra+)

10 Domain specification Estimation specification Point (or result) specification Refresh (partial) Refresh (concurrent) Process (I) Refresh (current) Process (II)

11 Refreshing and multi-processing Step 1: Definition of the "domain specification" – limits of the considered models Step 2: First estimation – Results define the "point specification" Step 3: Refreshing: definition of an "estimation specification" – between the results and the domain (by relaxing some constraints) Step 4: Next estimation – Results define a new "point specification"

12 RefreshingRelaxed constraints (cumulative) Current adjustmentNone (estimation spec = point spec) Current adjustment (partial)Coefficients of the regression variables Partial concurrent / ParametersParameters of the Arima model Partial concurrent / Last outliersLast outliers re-evaluated (1 year) Partial concurrent / OutliersAll outliers re-evaluated Partial concurrent / Outliers + ArimaArima model (orders) Concurrent adjustmentAll (estimation spec = domain spec)

13 SA Processing and refreshing. Tips Keep the domain specification as large as possible (for significant refreshing) Limitations of Demetra+ – Overview of the different specifications (→next release) – Possible problem with pre-specified outliers (→ use intervention variables when needed) – True current adjustment unavailable (→ JDemetra) – Limited set of refreshing:

14 4. File system of Demetra+ Storage of information in xml files Separate file for each document – Contents of the workspace – TramoSeats / X12 specification – TramoSeats / X12 single processing – Multi-processing – Calendars – User's variables

15 Files of a workspace

16 Contents of the workspace descriptor

17 Multi-processing file (in SAProcessing folder) Domain specification(s) Items – Attributes reference to domain specification[,estimation policy, quality] – Identification – [Data] – [Point specification] – [Estimation specification]

18 Remarks: – No results (except the estimated model) – All information for re-estimating the processing Identification Data All specifications – Future improvements of Demetra+ (refreshing): Comparison of the raw series Comparison of the models

19 5. WSACruncher WSACruncher is a console application for batch processing Read the workspace Refresh the processing Generate the output Save the results Demetra files (workspace) Demetra files (workspace) wsacruncher.params csv files...

20 The xml parameters file defines the main steps: – refreshing policy – output (csv, diagnostics) The workspace must contain all the files, using the same structure as Demetra+ Syntax of the command: \wsacruncher -x Example: " c:\program files...\wsacruncher" workspace.xml -x wsacruncher.params

21 6. Automation Best solution for production chains – making your in-house software Providing specific Demetra+/WSACruncher modules for – Accessing the data – Providing new diagnostics – Saving the results (Not discussed here) Using building blocks of Demetra+ in a new application – interacting with WSACruncher through xml files

22 Advanced? Xml files, WSACruncher.NET Applications (C#) VBA: Excel add-ins... Advanced users WSACruncher (params) Demetra+ Visual Studio (express edition) MS-Office Others (SAS...), through files NO YES IT-Team ? YES Light dev. ? YES NO

23 Automation: comparison SolutionAdvantagesDrawbacks WSACruncher Simple Efficient Limited possibilities.NET Powerful solution Complete access to internal routines For "professionals" only Uncertain future (JDemetra ?) VBA Light, accessible for non experts. Efficient MS solution ( JDemetra ?) No full access to routines of Demetra+ Xml files Independent solution Integration in legacy environments Complex (Rather) inefficient Limited access to routines of Demetra+


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