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
Profilers
•
Introduction to Profilers
•
Introduction to Profiling
• Profiler Features in JMP
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Profiler Features in JMP
There are several profiler facilities in JMP, accessible from a number of fitting platforms and the main menu under Graph. They are used to profile data column formulas.
Table 1.1
Profiler Features Summary
Description
Features
Prediction Profiler
Shows vertical slices across each factor, holding other factors at current values
Desirability, Optimization, Simulator, Propagation of Error
Contour Profiler
Horizontal slices show contour lines for two factors at a time
Simulator
Surface Profiler
3-D plots of responses for 2 factors at a time, or a contour surface plot for 3 factors at a time
Surface Visualization
Mixture Profiler
A contour profiler for mixture factors
Ternary Plot and Contours
Custom Profiler
A non-graphical profiler and numerical optimizer
General Optimization, Simulator
Excel Profiler
Visualize models (or formulas) stored in Excel worksheets.
Profile using Excel Models
Profiler availability is shown in
Table 1.2
. The Custom Profiler is available only through the Graph menu. (Model Comparison
does
have Custom Profiler available.)
Table 1.2
Where to Find JMP Profilers
Location
Profiler
Contour Profiler
Surface Profiler
Mixture Profiler
Graph Menu (as a Platform)
Yes
Yes
Yes
Yes
Fit Model: Least Squares
Yes
Yes
Yes
Yes
Fit Model: Generalized Regression
Yes
Fit Model: Mixed Model
Yes
Yes
Yes
Yes
Fit Model: Logistic
Yes
Fit Model: Loglinear Variance
Yes
Yes
Yes
Fit Model: Generalized Linear Model
Yes
Yes
Yes
Fit Model: Partial Least Squares
Yes
Neural
Yes
Yes
Yes
Model Comparison
Yes
Yes
Yes
Yes
Nonlinear: Factors and Response
Yes
Yes
Yes
Nonlinear: Parameters and SSE
Yes
Yes
Yes
Nonlinear: Fit Curve
Yes
Gaussian Process
Yes
Yes
Yes
Partial Least Squares
Yes
Life Distribution
Yes
Fit Life by X
Yes
Yes
Recurrence Analysis
Yes
Choice
Yes
Custom Design Prediction Variance
Yes
Yes
Note:
In this guide, we use the following terms interchangeably:
•
factor, input variable,
X
column, independent variable, setting, term
•
response, output variable,
Y
column, dependent variable, outcome
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Help created on 7/12/2018