| Name | Version | Summary | date |
| var-irf |
0.1.0 |
Impulse Response Function (IRF) computation and plotting utilities built on statsmodels VAR |
2025-10-25 00:26:58 |
| linearmodels |
7.0 |
Linear Panel, Instrumental Variable, Asset Pricing, and System Regression models for Python |
2025-10-21 13:42:22 |
| arch |
8.0.0 |
ARCH for Python |
2025-10-21 08:42:37 |
| rmcp |
0.5.1 |
Comprehensive Model Context Protocol server with 53 statistical analysis tools, universal operation approval system, and HTTP transport |
2025-10-20 23:00:24 |
| tsdisagg |
1.3.2 |
Temporal Disaggregation of Time Series Data in Python |
2025-10-13 23:49:37 |
| whittlehurst |
1.2 |
Hurst exponent estimation using Whittle's method |
2025-10-09 11:49:22 |
| evdsts |
1.0rc6 |
A Python implementation for retrieving and transforming macroeconomic time series data from TCMB EVDS (CBRT EDDS) API. |
2025-09-13 13:15:16 |
| cans-framework |
3.1.4 |
A production-ready deep learning framework for causal inference on structured, textual, and heterogeneous data |
2025-09-10 04:31:33 |
| pyelw |
0.9.1 |
Exact Local Whittle Estimation for Long Memory Time Series |
2025-09-04 21:17:07 |
| regularized-var |
0.1.1 |
Regularized Vector Autoregression (VAR) with ridge shrinkage, Minnesota prior, metrics, and walk-forward validation. |
2025-09-01 21:43:31 |
| dcmbench |
0.1.2 |
A comprehensive benchmarking framework for discrete choice models |
2025-08-29 17:35:21 |
| hfhvar |
0.1.1 |
HF-HVAR / HF-SVAR estimation and impulse responses with residual bootstrap |
2025-08-28 12:42:50 |
| x13-seasonal-adjustment |
0.1.3 |
Comprehensive X13-ARIMA-SEATS seasonal adjustment library for Python |
2025-08-28 12:31:24 |
| pyautocausal |
0.1.1 |
Automated causal inference pipelines for data scientists |
2025-08-24 19:00:30 |
| fin-nln |
0.1.0 |
A Python library for detecting nonlinearity in financial time series |
2025-08-19 17:35:37 |
| bellman-filter-dfsv |
1.0.0 |
High-performance JAX-based filtering for Dynamic Factor Stochastic Volatility (DFSV) models |
2025-08-12 01:10:38 |
| pystatar |
0.4.0 |
PyStataR aims to recreate and significantly enhance the top and most frequently used Stata commands in Python, transforming them into the most powerful and user-friendly statistical tools for academic research. Our goal is to not just replicate Stata's functionality, but to expand and improve upon it, leveraging Python's ecosystem to create superior research tools. |
2025-08-02 00:19:39 |
| pyoutreg |
0.1.1 |
A Python implementation of Stata's outreg2 for exporting regression results |
2025-08-02 00:05:34 |
| pyegen |
0.2.4 |
Python implementation of Stata's egen command for pandas DataFrames |
2025-07-30 23:18:29 |
| pyhtelasso |
0.2.0 |
A Python package for detecting treatment effect heterogeneity using debiased lasso |
2025-07-25 20:36:17 |