Book description
JMP 12 Specialized Models provides details about modeling techniques such as partitioning, neural networks, nonlinear regression, and time series analysis. Topics include the Gaussian platform, which is useful in analyzing computer simulation experiments. The book also covers the Response Screening platform, which is useful in testing the effect of a predictor when you have many responses.
Table of contents
- Contents
-
Learn about JMP
- Documentation and Additional Resources
- Formatting Conventions
-
JMP Documentation
- JMP Documentation Library
- Discovering JMP
- Using JMP
- Basic Analysis
- Essential Graphing
- Profilers
- Design of Experiments Guide
- Fitting Linear Models
- Specialized Models
- Multivariate Methods
- Quality and Process Methods
- Reliability and Survival Methods
- Consumer Research
- Scripting Guide
- JSL Syntax Reference
- JMP Help
- Additional Resources for Learning JMP
- Introduction to Specialized Modeling
-
Partition Models
- Use Decision Trees to Explore and Model Your Data
- Partitioning Overview
- Example of Partition
- Launching the Partition Platform
- Fit Group
- Partition Method
- Validation
- Graphs for Goodness of Fit
- Informative Missing
- Examples of Bootstrap Forest, Boosted Tree, and Model Comparison
- Statistical Details
- Neural Networks
- Model Comparison
- Nonlinear Regression with Built-In Models
- Nonlinear Regression with Custom Models
- Gaussian Process
- Time Series Analysis
-
Response Screening
- Screen Large-Scale Data
- Response Screening Platform Overview
- Example of Response Screening
- Launch the Response Screening Platform
- The Response Screening Report
- The PValues Data Table
- Response Screening Platform Options
- The Response Screening Personality in Fit Model
- Additional Examples of Response Screening
- Statistical Details
- References
- Index
Product information
- Title: JMP 12 Specialized Models
- Author(s):
- Release date: March 2015
- Publisher(s): SAS Institute
- ISBN: 9781629594767
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