Exploratory Analysis

Exploratory analysis methods examine data for trends, correlations, or other relationships. Sometimes, models are created which can later identify when new data does not follow the same trend as previous data (see, for example, using principal components analysis in multivariate statistical process control) or can be used to predict an amount of material or property (which is also discussed in Quantitative Regression Analysis.) Often, however, these methods are used simply to learn more about the data.

Top-Level Exploratory Analysis Functions

analysis - Graphical user interface for data analysis.

pca - Principal components analysis.

mcr - Multivariate curve resolution with constraints.

purity - Self-modeling mixture analysis method based on purity of variables or spectra.

corrspec - Resolves correlation spectroscopy maps.

crossval - Cross-validation for decomposition and linear regression.

evolvfa - Evolving factor analysis (forward and reverse).

ewfa - Evolving window factor analysis.

estimatefactors - Estimate number of significant factors in multivariate data.

wtfa - Window target factor analysis.

mlpca - Maximum likelihood principal components analysis.

coda_dw - Calculates values for the Durbin_Watson criterion of columns of data set.

coda_dw_interactive - Interactive version of CODA_DW.

comparelcms_sim_interactive - Interactive interface for COMPARELCMS.

trendtool - Univariate trend analysis tool.

cluster - KNN and K-means cluster analysis with dendrograms.

Multiway Analysis

analysis - Graphical user interface for data analysis.

mpca - Multi-way (unfold) principal components analysis.

gram - Generalized rank annihilation method.

parafac - Parallel factor analysis for n-way arrays.

parafac2 - Parallel factor analysis for unevenly sized n-way arrays.

tld - Trilinear decomposition.

tucker - Analysis for n-way arrays.

Multiway Utilities

outerm - Computes outer product of any number of vectors.

corcondia - Evaluates consistency of PARAFAC model.

coreanal - Analysis of the core array of a Tucker model.

corecalc - Calculate the Tucker3 core given the data array and loadings.

nassign - Generic subscript assignment indexing for n-way arrays.

nindex - Generic subscript indexing for n-way arrays.

unfoldm - Rearranges (unfolds) an augmented matrix to row vectors.

unfoldmw - Unfolds multiway arrays along specified order.

modelviewer - Visualization tool for multi-way models.

Application of Models to New Data

In most cases, the function used to create a model (e.g. PCA, PLS, etc) is also used to make a prediction with the created model. See the function used for more information on this. In addition, these utilities may be of use for certain applications.

modelselector - Create or apply a model selector model.

compressmodel - Remove references to unused variables from a model.

matchvars - Align variables of a dataset to allow prediction with a model.

pcapro - Projects new data on old principal components model.

Model Analysis and Calculation Utilities

manrotate - Graphical interface to manually rotate model loadings.

qconcalc - Calculate Q residuals contributions for predictions on a model.

residuallimit - Estimates confidence limits for sum squared residuals.

reviewmodel - Examines a standard model structure for typical problems.

tconcalc - Calculate Hotellings T2 contributions for predictions on a model.

tsqlim - Confidence limits for Hotelling's T^2.

varcap - Variance captured for each variable in PCA model.

varimax - Orthogonal rotation of loadings.

als - Alternating Least Squares computational engine.

datahat - Calculates the model estimate and residuals of the data.

dispmat - Calculates the dispersion matrix of two spectral data sets.

pcaengine - Principal Components Analysis computational engine.

tsqmtx - Calculates matrix for T^2 contributions for PCA.

comparelcms_simengine - Calculational Engine for comparelcms.

Plotting Utilities

modlrder - Displays model info for standard model structures.

plotloads - Extract and display loadings information from a model structure.

plotscores - Extract and display score information from a model.

ploteigen - Builds dataset object of eigenvalues/RMSECV information.

ssqtable - Displays variance captured table for model.

(Sub topic of Qualitative_Exploratory_Analysis_and_Classification)