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* Update generate_terminal_markdown.py * updates * update workflows * Automated Change * tests * tests * Automated Change * Update test_generate_docs.py * Automated Change * updates * Automated Change * Update gen-docs.yml * Update test.yml * Automated Change * Update test.yml * Automated Change * Update generate_sdk_markdown.py * Automated Change * test * Automated Change * testtt23 * Automated Change * Update generate_sdk_markdown.py * Automated Change * Automated Change * added empting reference folders before autogen docs * updates * Automated Change * update tests gitactions * Automated Change * up * Automated Change * Automated Change * update pytest * Automated Change * tests * Automated Change * examples update * Automated Change * Update generate_sdk_markdown.py * Automated Change * Update test.yml * Update generate_sdk_markdown.py * strip * Automated Change * Workflow : check test update * Automated Change * Automated Change * Automated Change * Update test.yml * Automated Change * Update test.yml * Automated Change * Automated Change * up * Automated Change * Update generate_sdk_markdown.py * Automated Change * update workflows * fix guides * testing * Update gh-pages.yml * Update gh-pages.yml Co-authored-by: tehcoderer <tehcoderer@users.noreply.github.com> Co-authored-by: Jeroen Bouma <jer.bouma@gmail.com> Co-authored-by: Chavithra PARANA <chavithra@gmail.com> Co-authored-by: Chavithra <Chavithra@users.noreply.github.com> Co-authored-by: jose-donato <43375532+jose-donato@users.noreply.github.com> Co-authored-by: jose-donato <jose-donato@users.noreply.github.com>
2.6 KiB
Vendored
2.6 KiB
Vendored
title, description
| title | description |
|---|---|
| autoets | OpenBB Terminal Function |
autoets
Perform Automatic ETS (Error, Trend, Seasonality) forecast: https://nixtla.github.io/statsforecast/examples/getting_started_with_auto_arima_and_ets.html
Usage
autoets [--naive] [-d {}] [-c TARGET_COLUMN] [-n N_DAYS] [-s {N,A,M}] [-p SEASONAL_PERIODS] [-w START_WINDOW] [--end S_END_DATE] [--start S_START_DATE] [--residuals] [--forecast-only] [--export-pred-raw]
Parameters
| Name | Description | Default | Optional | Choices |
|---|---|---|---|---|
| naive | Show the naive baseline for a model. | False | True | None |
| target_dataset | The name of the dataset you want to select | None | True | None |
| target_column | The name of the specific column you want to use | close | True | None |
| n_days | prediction days. | 5 | True | None |
| seasonal | Seasonality: N: None, A: Additive, M: Multiplicative. | A | True | N, A, M |
| seasonal_periods | Seasonal periods: 4: Quarterly, 7: Daily | 7 | True | None |
| start_window | Start point for rolling training and forecast window. 0.0-1.0 | 0.85 | True | None |
| s_end_date | The end date (format YYYY-MM-DD) to select for testing | None | True | None |
| s_start_date | The start date (format YYYY-MM-DD) to select for testing | None | True | None |
| residuals | Show the residuals for the model. | False | True | None |
| forecast_only | Do not plot the historical data without forecasts. | False | True | None |
| export_pred_raw | Export predictions to a csv file. | False | True | None |
Examples
2022 Oct 21, 18:20 (🦋) /forecast/ $ load AAPL
2022 Oct 21, 18:21 (🦋) /forecast/ $ autoets AAPL
Actual price: 143.39
┏━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Datetime ┃ Prediction ┃
┡━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│ 2022-10-21 │ 143.42 │
├────────────┼────────────┤
│ 2022-10-24 │ 143.42 │
├────────────┼────────────┤
│ 2022-10-25 │ 143.42 │
├────────────┼────────────┤
│ 2022-10-26 │ 143.42 │
├────────────┼────────────┤
│ 2022-10-27 │ 143.42 │
└────────────┴────────────┘
