Plotting Analysis Aids and I O Functions and Modeling Function Overview: Difference between pages
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''' | '''High-Level Modeling Functions''' | ||
The following output a model structure (or similar) and are generally considered "high-level" modeling functions designed for relatively simple use by less-experienced users as well as expert users. | |||
:[[analysis]] - Graphical user interface for data analysis. | :[[analysis]] - Graphical user interface for data analysis. | ||
:[[ | :[[caltransfer]] - Create or apply calibration and instrument transfer models. | ||
:[[ | :[[cluster]] - KNN and K-means cluster analysis with dendrograms. | ||
:[[ | :[[cls]] - Classical Least Squares regression for multivariate Y. | ||
:[[ | :[[corrspec]] - Resolves correlation spectroscopy maps. | ||
:[[ | :[[frpcr]] - Full-ratio PCR calibration and prediction. | ||
:[[ | :[[knn]] - K-nearest neighbor classifier. | ||
:[[ | :[[lwr]] - Locally weighted regression for univariate Y. | ||
:[[ | :[[mcr]] - Multivariate curve resolution with constraints. | ||
:[[ | :[[mlr]] - Multiple Linear Regression for multivariate Y. | ||
:[[ | :[[modelselector]] - Create or apply a model selector model. | ||
:[[ | :[[mpca]] - Multi-way (unfold) principal components analysis. | ||
:[[npls]] - Multilinear-PLS (N-PLS) for true multi-way regression. | |||
:[[parafac]] - Parallel factor analysis for n-way arrays. | |||
:[[parafac2]] - Parallel factor analysis for unevenly sized n-way arrays. | |||
:[[pca]] - Principal components analysis. | |||
:[[pcr]] - Principal components regression for multivariate Y. | |||
:[[pls]] - Partial least squares regression for multivariate Y. | |||
:[[plsda]] - Partial least squares discriminant analysis. | |||
:[[purity]] - Self-modeling mixture analysis method based on purity of variables or spectra. | |||
:[[simca]] - Soft Independent Method of Class Analogy. | |||
:[[tld]] - Trilinear decomposition. | |||
:[[tucker]] - Analysis for n-way arrays. | |||
'''Medium-Level Modeling Functions''' | |||
The following provide functionality not generally available through another higher-level function and may be of use for certain analysis methods but also require more knowledge of Matlab and the methods involved. | |||
:[[gram]] - Generalized rank annihilation method. | |||
:[[mlpca]] - Maximum likelihood principal components analysis. | |||
:[[coda_dw]] - Calculates values for the Durbin_Watson criterion of columns of data set. | |||
:[[comparelcms_sim_interactive]] - Interactive interface for COMPARELCMS. | |||
:[[cr]] - Continuum Regression for multivariate y. | |||
:[[evolvfa]] - Evolving factor analysis (forward and reverse). | |||
:[[ | :[[ewfa]] - Evolving window factor analysis. | ||
:[[ | :[[glsw]] - Generalized least-squares weighting/preprocessing. | ||
:[[ | :[[gram]] - Generalized rank annihilation method. | ||
:[[lwrpred]] - Engine for locally weighted regression models. | |||
:[[ | :[[mlpca]] - Maximum likelihood principal components analysis. | ||
:[[ | :[[polypls]] - PLS regression with polynomial inner-relation. | ||
:[[ridge]] - Ridge regression by Hoerl-Kennard-Baldwin. | |||
:[[ | :[[wtfa]] - Window target factor analysis. | ||
:[[ | |||
:[[ | |||
:[[ | |||
:[[ | |||
:[[ | |||
:[[ | |||
:[[ | |||
:[[ | |||
(Sub topic of [[Categorical_Index|Categorical_Index]]) | (Sub topic of [[Categorical_Index|Categorical_Index]]) |
Revision as of 11:21, 1 September 2010
High-Level Modeling Functions The following output a model structure (or similar) and are generally considered "high-level" modeling functions designed for relatively simple use by less-experienced users as well as expert users.
- analysis - Graphical user interface for data analysis.
- caltransfer - Create or apply calibration and instrument transfer models.
- cluster - KNN and K-means cluster analysis with dendrograms.
- cls - Classical Least Squares regression for multivariate Y.
- corrspec - Resolves correlation spectroscopy maps.
- frpcr - Full-ratio PCR calibration and prediction.
- knn - K-nearest neighbor classifier.
- lwr - Locally weighted regression for univariate Y.
- mcr - Multivariate curve resolution with constraints.
- mlr - Multiple Linear Regression for multivariate Y.
- modelselector - Create or apply a model selector model.
- mpca - Multi-way (unfold) principal components analysis.
- npls - Multilinear-PLS (N-PLS) for true multi-way regression.
- parafac - Parallel factor analysis for n-way arrays.
- parafac2 - Parallel factor analysis for unevenly sized n-way arrays.
- pca - Principal components analysis.
- pcr - Principal components regression for multivariate Y.
- pls - Partial least squares regression for multivariate Y.
- plsda - Partial least squares discriminant analysis.
- purity - Self-modeling mixture analysis method based on purity of variables or spectra.
- simca - Soft Independent Method of Class Analogy.
- tld - Trilinear decomposition.
- tucker - Analysis for n-way arrays.
Medium-Level Modeling Functions The following provide functionality not generally available through another higher-level function and may be of use for certain analysis methods but also require more knowledge of Matlab and the methods involved.
- gram - Generalized rank annihilation method.
- mlpca - Maximum likelihood principal components analysis.
- coda_dw - Calculates values for the Durbin_Watson criterion of columns of data set.
- comparelcms_sim_interactive - Interactive interface for COMPARELCMS.
- cr - Continuum Regression for multivariate y.
- evolvfa - Evolving factor analysis (forward and reverse).
- ewfa - Evolving window factor analysis.
- glsw - Generalized least-squares weighting/preprocessing.
- gram - Generalized rank annihilation method.
- lwrpred - Engine for locally weighted regression models.
- mlpca - Maximum likelihood principal components analysis.
- polypls - PLS regression with polynomial inner-relation.
- ridge - Ridge regression by Hoerl-Kennard-Baldwin.
- wtfa - Window target factor analysis.
(Sub topic of Categorical_Index)