Habilidades statsmodels
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statsmodels
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使用statsmodels进行统计分析
Também disponível em: K-Dense-AI
用户需要使用严格的统计方法分析数据。此技能为回归模型、假设检验、时间序列分析和诊断程序提供全面指导。
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A utilizar "statsmodels". 拟合OLS模型预测房价，特征为面积和卧室数量。
Resultado esperado:
- 模型摘要显示R²为0.75，表明解释了75%的方差
- 面积系数：+250（每增加一平方英尺，房价增加250美元）
- 卧室系数：+15000（每增加一个卧室，房价增加15,000美元）
- P值均在p < 0.05水平上显著
- Breusch-Pagan检验P值为0.42，表明无异方差问题
- 条件数为12，表明无多重共线性问题
A utilizar "statsmodels". 预测未来30天具有季节性模式的销售数据。
Resultado esperado:
- SARIMAX(1,1,1)(1,1,1,7)模型拟合用于周季节性
- ADF检验确认差分后的平稳性
- Ljung-Box检验P值为0.35，表明无残差自相关
- 30天预测显示周末的预期季节性增长
- 95%预测区间随时间扩大，反映预测不确定性
A utilizar "statsmodels". 构建逻辑回归模型预测客户流失。
Resultado esperado:
- Logit模型在28次迭代后成功收敛
- 合同类型系数：-1.2（月度合同流失率较低）
- 月费用系数：+0.05（费用越高，流失风险越大）
- 优势比显示合同类型对流失的影响最大
- AUC为0.82，表明良好的区分能力
Auditoria de Segurança
Segurov5 • 1/17/2026
Pure documentation skill containing statistical modeling reference material. All 421 static findings are FALSE POSITIVES: markdown code formatting backticks misinterpreted as shell commands, Python import statements in documentation examples flagged as dynamic imports, and statistical terminology (ARIMA, VAR, heteroskedasticity) misidentified as security keywords. No executable code, no network operations, no file system access beyond own directory.
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⚡ Contém scripts (6)
⚙️ Comandos externos (352)
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Conformidade com especificações
O Que Você Pode Construir
回归分析
构建和比较回归模型以进行预测分析和推断。
统计推断
进行假设检验并使用综合诊断验证假设。
时间序列预测
分析时间模式并使用ARIMA及相关模型进行预测。
Tente Estes Prompts
基础回归
展示如何使用statsmodels和pandas DataFrame拟合OLS回归模型。包括如何添加常数项和解释结果摘要。
时间序列
帮助我构建ARIMA模型进行时间序列预测。包括如何检查平稳性、选择参数以及生成带置信区间的预测。
逻辑回归
展示如何在statsmodels中拟合逻辑回归模型进行二分类。包括如何计算优势比和边际效应。
模型诊断
帮助我对回归模型进行诊断检验。包括异方差性、残差正态性和多重共线性检验。
Melhores Práticas
- 始终使用sm.add_constant()添加常数项以估计截距
- 在解释模型之前使用诊断检验检查模型假设
- 当存在异方差或聚类问题时使用稳健标准误
- 使用交叉验证或留出数据验证预测结果
Evitar
- 忘记添加常数项（模型中无截距）
- 对二元结果使用OLS（应使用逻辑回归）
- 在不考虑链接函数的情况下解释系数
- 忽视泊松模型中的过度分散
Perguntas Frequentes
statsmodels与scikit-learn相比如何？
Statsmodels专注于统计推断，提供详细的P值和诊断结果。Scikit-learn专注于预测。当需要解释性时使用statsmodels。
支持的最大模型大小是多少？
Statsmodels处理适合内存的数据集。大型数据集可能需要采样或分块处理。实际限制取决于可用的RAM。
我可以将statsmodels与pandas DataFrame一起使用吗？
是的，statsmodels与pandas无缝集成。列名变成变量名，结果对象包含DataFrame兼容的输出。
使用statsmodels时我的数据安全吗？
Statsmodels在本地内存中处理数据。数据不会离开您的机器。分析过程中不建立外部连接。
为什么我的模型不收敛？
收敛问题通常源于逻辑模型中的完美分离、多重共线性或缩放问题。尝试缩放预测变量或使用正则化。
何时应该使用GLS而不是OLS？
当误差具有已知的非恒定方差（WLS）或存在相关性时（用于时间序列的GLSAR），使用GLS。否则，使用带稳健标准误的OLS通常就足够了。
Detalhes do Desenvolvedor
Autor
davila7Licença
MIT
Repositório
https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/scientific/statsmodelsReferência
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