Release Notes Version 8 0

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Revision as of 15:36, 10 June 2015 by imported>Scott
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Version 8.0 of PLS_Toolbox and Solo was released in June, 2015.

For general product information, see PLS_Toolbox Product Page. For information on Solo, see Solo Product Page.

(back to Release Notes PLS Toolbox and Solo)

New Features in Solo and PLS_Toolbox

Analysis and Models

  • MLSCA - Multi-level simultaneous component analysis.
  • History now captured in history field of Model Object.
  • ANN now supports custom cross-validation.
  • PLSDA varcap plot now available.
  • Better handle full-rank PCA sub-models where Q residuals are zero in simca.

Plotting

  • Improve handling of zoom status in newer versions of Matlab.
  • Better handling of font sizes.
  • Smarter plot style (e.g., scatter vs. bar) assumptions in "automatic" mode.

Importers

  • omnicreadr - Reads OMNICix HDF5 image files.
  • Improved importer behavior with mixed length data using matchvars during import.
  • Updated libraries for Horiba file formats including 64 bit.

Preprocessing

  • glog Generalized Log Transform added to preprocessing options.
  • pqnorm Probabilistic Quotient Normalization added to preprocessing options.
  • ******{REV r19390} glsw Combine ELS/EMM and EPO options (use "inf" to select all PCs to get old ELS behavior)
  • Add support for handling missing data in both normaliz and mscorr (median only).

Distribution Fitting Toolbox

  • kurtosis: Added kurtosis statistic function.
  • skewness: Added skewness statistic function.

Other Interfaces

  • Multiblock Tool - Interface to view, manipulate, and join data.
  • Model Optimizer - Better handling of numeric data in comparison table, additional statistics, and improved handling of include field.


New Command-line Features and Functions

Misc New Functions

  • mlsca Multi-level Simultaneous Component Analysis.
  • multiblock Create or apply a multiblock model for joining data.

Command-Line Changes

  • matchvars - Add logic to speed up some cases of joins.
  • mdcheck - Allow use of KNN as data replacement method (replace missing data with data from sample(s) which are closest).
  • jmlimit - Better handle degenerate cases when multiple confidence levels are requested (return VECTOR of zeros instead of single zero).