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 BuiltIn Models
 Nonlinear Regression with Custom Models
 Gaussian Process
 Time Series Analysis

Response Screening
 Screen LargeScale 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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