JMP 14.2 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 13.2 Online Documentation
Design of Experiments Guide
• Custom Designs
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Custom Designs
Construct Designs That Meet Your Needs
Use the Custom Design platform to construct optimal designs that are custom built for your specific experimental setting. Generally, a custom design is more cost-effective than a design obtained using alternative methods. You can perform the following tasks:
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Enter factors of many different types.
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Specify constraints on the design space.
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Indicate which effects are necessary to estimate and which are desirable to estimate, if possible, given the number of runs.
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Specify a number of experimental runs that matches your budget.
The Custom Design platform constructs a wide variety of designs, including these special design types: Screening, Response Surface, Mixture, Random Block, Split Plot, Split-Split-Plot, and Two-Way Split Plot.
This chapter contains a detailed example of how to use the Custom Design platform, followed by information about the platform. See also the
Examples of Custom Designs topic
.
Figure 4.1
Color Map for Absolute Correlations
Contents
Overview of Custom Design
Example of a Custom Design
Create the Design
Analyze the Data
Custom Design Window
Responses
Factors
Define Factor Constraints
Model
Alias Terms
Design Generation
Design
Design Evaluation
Output Options
Custom Design Options
Description of Options
Simulate Responses
Save X Matrix
Number of Starts
Design Search Time
Set Delta for Power
Technical Details for Custom Designs
Designs with Randomization Restrictions
Covariates with Hard-to-Change Levels
Numbers of Whole Plots and Subplots
Optimality Criteria
D-Efficiency
Coordinate-Exchange Algorithm
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Help created on 3/19/2020