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404 JMP Starter Appendix A
The Multivariate Category
equal intervals between time periods. Time Series plots the time series and autocorrelations,
shows a variogram, and shows the spectral density.
“Time Series Analysis” of JMP Statistics and Graphics Guide discusses time series analysis and
gives examples and statistical details
Categorical Clicking the Categorical button, choosing Analyze > Modeling > Categorical,
does tabulation and summarization of categorical response data, including multiple response
data, and calculates test statistics.
See the JMP Statistics and Graphics Guide for more details categorical response analysis.
Partition Clicking the Partition button, or choosing Analyze > Modeling > Partition, recursively
partitions rows into groups according to x-values that associate with y-values. This partitioning
creates a tree of partitions. The factor columns (x) can be either continuous or categorical
(nominal or ordinal).
See the JMP Statistics and Graphics Guide for details about the Partition platform.
Neural Net Clicking the Neural Net button, or choosing Analyze > Modeling > Neural Net, fits
a single layer neural network. The neural network is a set of nonlinear equations that predict
output variables (y) from input variables (x) in a flexible way using layers of linear regressions and
S-shaped functions. JMP fits the neural net using standard nonlinear least squares regression
methods.
See the JMP Statistics and Graphics Guide for details about Neural Nets.
Gaussian Process Clicking the Gaussian Process button, or choosing Analyze > Modeling >
Gaussian Process, models the relationship between a continuous response and one or more
continuous predictors. The Gaussian Process platform fits a spatial correlation model to the data,
where the correlation of the response between two observations decreases as the values of the
independent variables become more distant.
See the JMP Statistics and Graphics Guide for details about Gaussian processes.
Choice Clicking the Choice button, or choosing Analyze > Modeling > Choice, makes
probabilistic predictions regarding human choice. It is particularly valuable in marketing research
and product design. The Choice platform is designed for use in market research experiments.
See the JMP Statistics and Graphics Guide for details about Choice models.
The Multivariate Category
The Multivariate category introduces ways to look at continuous variables when they are considered as
responses only; there are no factor or independent variables. Multivariate exploration with correlations
and cluster analysis lets you look at many variables at the same time.