Forecasting on English AI Terms Dictionary

Time series

Sat, 18 Jul 2026 10:18:23 +0000

Definition

Time series data consists of observations recorded sequentially over time intervals. In AI, this data type is crucial for predicting future trends based on historical patterns. Specialized models like ARIMA, LSTM, and Transformer-based architectures are employed to capture temporal dependencies, seasonality, and trends. Accurate time series analysis enables applications ranging from stock market prediction to energy consumption forecasting and sensor data monitoring.

Summary

A sequence of data points indexed in time order, commonly analyzed using specialized AI models for forecasting.

Bayesian structural time series

Sat, 18 Jul 2026 09:48:06 +0000

Definition

Bayesian structural time series (BSTS) models represent time series data as a sum of interpretable components such as trend, seasonality, and regression effects, while accounting for uncertainty through Bayesian inference. By placing priors on these components, BSTS allows for robust forecasting and causal impact estimation. This method is widely used in econometrics and marketing analytics to understand the effect of interventions on time-dependent outcomes, providing credible intervals for predictions rather than point estimates.