Skills

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SKILL.md

---
name: ambric
description: >
  Augmented Mixed-frequency Bayesian Regional Inference with Constraints. Use when writing Python code that uses the ambric package.
license: MIT
compatibility: Requires Python >=3.12.
---

# ambric

Augmented Mixed-frequency Bayesian Regional Inference with Constraints

## Installation

```bash
pip install ambric
```

## API overview

### Classes

Main classes provided by the package

- `Ambric`: Augmented Mixed-frequency Bayesian Regional Inference with Constraints

### Ambric Methods

Methods for the Ambric class

- `Ambric.__repr__`
- `Ambric.fit`
- `Ambric.save_trace`
- `Ambric.populate_results`
- `Ambric.plot_national_quarterly_vs_implied`
- `Ambric.plot_regional_annual_estimate`
- `Ambric.plot_single_region_annual_estimate`
- `Ambric.plot_estimated_regional_quarterly`
- `Ambric.plot_current_nowcast`
- `Ambric.assemble_loadings_data`
- `Ambric.plot_loadings_by_region`
- `Ambric.plot_loadings_aggregate`
- `Ambric.bands_indicator`
- `Ambric.point_estimates_q_on_4q`
- `Ambric.point_estimates_q_on_q`
- `Ambric.to_index_q_on_q`
- `Ambric.seasonally_adjusted_index_and_growth_by_region`

### Functions

Utility functions

- `bands_indicator_out_of_sample_results`: Bands classification of out-of-sample trend q-on-q nowcasts
- `build_ambric_model`: Build the AMBRIC Bayesian state-space model
- `diagnostics.oos_q_on_4q_performance_table`
- `diagnostics.plot_out_of_sample_nowcasts`
- `diagnostics.plot_out_of_sample_rmse`
- `plot_seasonally_adjusted_q_on_q_growth`: _summary_
- `prep_data_for_model_run`: Expects a data frame in following format:
- `run_out_of_sample_exercise`: Run out-of-sample exercise to evaluate model performance
- `trace_to_series`: Convert a trace to the relevant estimated series coming out of the model
- `trend_adjust_out_of_sample_results`
- `utilities.generate_realistic_simulated_data`
- `utilities.simulate_data`
- `utilities.simulate_real_time_data`

### Constants

Module-level constants and data

- `utilities.OMEGA`

## Resources

- [llms.txt](llms.txt) — Indexed API reference for LLMs
- [llms-full.txt](llms-full.txt) — Comprehensive documentation for LLMs