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数据与复现
ST
statsmodels
维护者 K-Dense Inc. · 最近更新 2026年4月1日
statsmodels：Statsmodels is Python's premier 库 ，用于 statistical modeling，providing tools ，用于 estimation，inference，、 diagnostics across wide range of statistical methods。 Apply this skill ，用于 rigorous 统计分析，，面向 simple linear 回归 to complex time series models 、 econometric analyses。
原始来源
K-Dense-AI/claude-scientific-skills
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/statsmodels
- 维护者
- K-Dense Inc.
- 许可
- BSD-3-Clause license
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- Statsmodels is Python's premier 库 ，用于 statistical modeling，providing tools ，用于 estimation，inference，、 diagnostics across wide range of statistical methods. Apply this skill ，用于 rigorous 统计分析，，面向 simple linear 回归 to complex time series models 、 econometric analyses。
- X = sm.add_constant(X_data)。
原始文档
SKILL.md 摘录
When to Use This Skill
This skill should be used when:
- Fitting regression models (OLS, WLS, GLS, quantile regression)
- Performing generalized linear modeling (logistic, Poisson, Gamma, etc.)
- Analyzing discrete outcomes (binary, multinomial, count, ordinal)
- Conducting time series analysis (ARIMA, SARIMAX, VAR, forecasting)
- Running statistical tests and diagnostics
- Testing model assumptions (heteroskedasticity, autocorrelation, normality)
- Detecting outliers and influential observations
- Comparing models (AIC/BIC, likelihood ratio tests)
- Estimating causal effects
- Producing publication-ready statistical tables and inference
Linear Regression (OLS)
import statsmodels.api as sm
import numpy as np
import pandas as pd
## Fit OLS model
model = sm.OLS(y, X)
results = model.fit()
适用场景
- Fitting 回归 models (OLS，WLS，GLS，quantile 回归)。
- Performing generali。
不适用场景
- Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。
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