ARIMA与平滑
31 种方法属于此方法族。
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ARIMA（自回归积分滑动平均）模型ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series fro自回归积分滑动平均模型 (ARIMA)The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and mo自回归移动平均模型 (ARMA)The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a mETS：误差、趋势、季节性指数平滑ETS is a comprehensive exponential smoothing framework that automatically selects additive or multiplicative combinations of the error (E), trend (T) and seasonal (S) components ofETSformer：用于时间序列预测的指数平滑Transformer模型ETSformer is a deep learning architecture for time-series forecasting introduced by Woo et al. in 2022. It integrates classical exponential smoothing principles directly into the T简单和双指数平滑 (SES / Holt)Exponential smoothing is a family of basic time-series forecasting models in which each new observation updates a smoothed estimate by a weighting parameter. Simple exponential smo
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全部方法 31
ARIMA（自回归积分滑动平均）模型自回归积分滑动平均模型 (ARIMA)自回归移动平均模型 (ARMA)ETS：误差、趋势、季节性指数平滑ETSformer：用于时间序列预测的指数平滑Transformer模型简单和双指数平滑 (SES / Holt)傅里叶自回归积分滑动平均模型傅里叶自回归移动平均模型傅里叶季节性自回归积分移动平均模型 (Fourier SARIMA Model)霍尔特-温特斯三指数平滑法移动平均（MA）模型多层和混合效应模型的功效分析非线性自回归积分移动平均模型非线性自回归移动平均模型 (NARMA)非线性季节性自回归积分滑动平均模型面板ARIMA模型面板自回归移动平均模型面板季节性自回归积分滑动平均模型稳健 ARIMA 模型稳健自回归滑动平均模型稳健SARIMA模型稳健时间序列分析季节性ARIMA（SARIMA）SARIMA模型SARIMAX结构断点 ARIMA 模型结构断裂季节性自回归积分移动平均模型时变参数自回归积分滑动平均模型 (TVP-ARIMA)时变参数自回归滑动平均模型 (TVP-ARMA)时变参数SARIMA模型 (TVP-SARIMA)X-13ARIMA-SEATS 季节调整