Introduction | Set-up & Data | Temporal disaggregation and interpolation methods | Chow-Lin, Fernandez and Litterman | Model-based Denton | Autoregressive Distributed Lag (ADL) Models | Reverse regression | Benchmarking methods | Denton | Growth rate preservation (GRP) | Cubic splines | Cholette | Reconciliation and multivariate temporal disaggregation | Multivariate Cholette | Multivariate Chow-Lin and Fernandez | Calendarization | Calendarization with Denton | References

Introduction | Conclusions

Launch the 'JWSACruncher" | Create the parameter file with create_param_file() | To run the JWSACruncher

Introduction | Installation settings | Usage | 1. Prepare and import data | 2. Create/Update model | 2.1. Create a new model | 2.2. Update an existing model | 2.3. Composition of the created object | 3. Estimation | 3.1. Different algorithms/functions | 3.2. Prior standardization of the data | 3.3. Fixed parameters | 3.4. Save R object from one time to another | 4. Results | 4.1. Estimates | 4.2. Forecasts | 4.3. News analysis | References

Seasonal adjustment specification | Add the result of the seasonal adjusment | Add the outliers to the plot | Add the ARIMA model | Add a table with some diagnostics | Use existing model

Introduction | Installation settings | Usage | Input data | Format 1: long view | Format 2: vertical view | Format 3: horizontal view | Processing | Details on the main functions | Vintages & revisions | Revision analysis & reporting | Output | User-defined thresholds | Tests description and interpretation | Relevancy | Theil’s Inequality Coefficient | Bias | T-test and Augmented T-test | Slope and drift | Efficiency | Regression of revisions on previous estimates | Regression of revisions from latter vintages on revisions from the previous vintages | Orthogonality | Regression of latter revisions (Rv) on previous revisions (Rv_1, Rv_2,...Rv_p) | Regression of latter revisions (Rv) on revisions from a specific vintage (Rv_k) | Test of autocorrelations in revisions | Test of seasonality in revisions | Signal vs Noise | References

X-13-ARIMA model | TRAMO-SEATS model | Directly create a R Markdown file | Reproductibility

Importer des données depuis un tableur | Exporter les données depuis R vers un tableur

X-13-ARIMA model | TRAMO-SEATS model | Directly create a R Markdown file | Reproductibility