JMP 14.0 Online Documentation (English)
Discovering JMP
Using JMP
Basic Analysis
Essential Graphing
Profilers
Design of Experiments Guide
Fitting Linear Models
Predictive and Specialized Modeling
Multivariate Methods
Quality and Process Methods
Reliability and Survival Methods
Consumer Research
Scripting Guide
JSL Syntax Reference
JMP iPad Help
JMP Interactive HTML
Capabilities Index
JMP 13 Online Documentation
JMP 12 Online Documentation
Predictive and Specialized Modeling
• Time Series Analysis
Previous
•
Next
Time Series Analysis
Fit Time Series Models and Transfer Functions
The Time Series platform enables you to explore, analyze, and forecast univariate time series. A time series is a set of observations taken over a series of equally spaced time periods. Observations that are close together in time are typically correlated. Time series methodology takes advantage of this dependence between observations to better predict what the series will look like in the future.
Characteristics that are common in time series data include seasonality, trend, and autocorrelation. The Time Series platform provides options to handle these characteristics. Graphs such as variograms, autocorrelation plots, partial autocorrelation plots, and spectral density plots can be used to identify the type of model appropriate for describing and predicting (forecasting) the time series. There are also several decomposition methods in the platform that enable you to remove seasonal or general trends in the data to simplify the analysis. Alternatively, the platform can fit more sophisticated ARIMA models that have the ability to incorporate seasonality and long term trends all in one model.
The Time Series platform can also fit transfer function models when supplied with an input series.
Figure 15.1
Forecast Plot
Contents
Overview of the Time Series Platform
Example of the Time Series Platform
Launch the Time Series Platform
The Time Series Analysis Report
Time Series Graph
Time Series Basic Diagnostics Chart
Time Series Platform Options
Time Series Diagnostics
Differencing and Decomposition
ARIMA and Seasonal ARIMA Models
Smoothing Models
Transfer Function Models
Smoothing Model Specification Windows
Reports
Difference Report
Decomposition Reports
Model Comparison Report
Model Report
Transfer Function Report
Spectral Density Report
Additional Example of the Time Series Platform
Statistical Details for the Time Series Platform
Statistical Details for Spectral Density
Statistical Details for X-11 Decomposition
Statistical Details for Smoothing Models
Statistical Details for ARIMA Models
Statistical Details for Transfer Functions
Previous
•
Next
Help created on 7/12/2018