Time-series model
A time-series model represents or analyzes observations ordered over time to characterize temporal patterns or dependencies and support inference or prediction.
Effective Data Analysis
A time series model uses observations ordered over time to estimate or predict future values while accounting for temporal patterns.
- How it is used
- Forecasts future values from historical observations for time-indexed questions in areas such as business, energy, and health.
- How deep it goes
- Identifies seasonality, trend, and noise as forecasting components, but does not detail model fitting.
- Examples
- Uses examples of electricity consumption, holiday-aware retail sales, hospitalizations, and revenue forecasts.
- What you can do after
- Apply it to forecast values for future periods, such as daily electricity use or weekly sales.
Read how Effective Data Analysis explains time-series model →
Statistics Every Programmer Needs
A time series model describes observations indexed over time and their temporal dependencies or patterns.
- How it is used
- Uses temporal patterns and dependencies to understand past observations and forecast future values.
- How deep it goes
- Defines temporal modeling and summarizes ARIMA and smoothing components, without detailing model fitting or evaluation.
- Examples
- Applies forecasting to stock prices, retail demand, traffic patterns, and energy consumption.
- What you can do after
- Understand temporal patterns and forecast future values in sequential data.
Read how Statistics Every Programmer Needs explains time-series model →
Related concepts
- seasonality effectuses · A seasonality effect is a recurring pattern of variation in data associated with regular temporal, calendar, or time-of-year cycles.
- forecast baselineproduces · A reference forecast generated by a forecasting process against which demand planning decisions or improved forecasts can be compared.
- judgmental forecastcontrasts with · A judgmental forecast is a prediction of future demand that incorporates human assessment rather than relying solely on an automated forecasting model.
- demand forecastcontrasts with · A demand forecast is an estimate or prediction of the quantity of a product, service, or resource that will be needed during a specified future period.
- trenduses · A trend is a developing or persistent direction, pattern, or movement in observations, conditions, behavior, or attention.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.