v. 0.9.3

• Fixed a bug in multiclass PLS-DA leading to wrong classification results when class names in reference variable (factor) were not in alphabetical order

v. 0.9.2

• improvements to ipls() method plus fixed a bug preventing breaking the selection loop (#56)
• fixed a bug in selectCompNum() related to use of Wold criterion (#57)
• fixed a bug with using of max.cov parameter in prep.autoscale() (#58)
• default max.cov value in prep.autoscale() is set to 0 (to avoid scaling only of constant variables)
• code refactoring and small improvements
• added tests for prep.autoscale()

v. 0.9.1

• all plot functions have new opacity parameter for semi-transparent colors
• several improvements to PLS-DA method for one-class discrimination
• fixed a bug with wrong estimation of maximum number of components for PCA/SIMCA with cross-validation
• added chapter on PLS-DA to the tutorial (including last improvements)

v. 0.9.0

• added randomized PCA algorithm (efficient for datasets with large number of rows)
• added option to inherit and show critical limits on residuals plot for PCA/SIMCA results
• added support for data driven approach to PCA/SIMCA (DD-SIMCA)
• added calculation of class belongings probability for SIMCA results
• added plotExtreme() method for SIMCA models
• added setResLimits() method for PCA/SIMCA models
• added plotProbabilities() method for SIMCA results
• added getConfusionMatrix() method for classification results
• added option to show prediction statistics using plotPrediction() for PLS results
• added option to use equal axes limits in plotPrediction() for PLS results
• the tutorial has been amended and extended correspondingly

v. 0.8.4

• small improvements to calculation of statistics for regression coefficients
• pls.getRegCoeffs() now also returns standard error and confidence intervals calculated for unstandardized variables
• new method summary() for object with regression coefficients (regcoeffs)
• fixed a bug with double labels on regression coefficients plot with confidence intervals
• fixed a bug in some PLS plots where labels for cross-validated results forced to be numbers
• when using mdaplot for data frame with one or more factor columns, the factors are now transofrmed to dummy variables (before it led to an error)
• Bookdown documentation has been updates accordingly

v. 0.8.3

• fixed a bug in mdaplot when using a factor with more than 8 levels for color grouping led to an error
• fixed a bug in pca led to an error when using NIPALS (bug in calculation of eigenvalues)
• bars on a bar plot now can be color grouped

v. 0.8.2

• parameters lab.cex and lab.col now are also applied to colorbar labels

v. 0.8.1

• fixed a bug in PCA when explained variance was calculated incorrectly for data with excluded rows
• fixed several issues with SIMCA (cross-validation) and SIMCAM (Cooman's plot)
• added a chapter about SIMCA to the tutorial

v. 0.8.0

• tutorial has been moved from GitBook to Bookdown and fully rewritten
• GitHub repo for the package has the tutorial as a static html site in docs folder
• the mdaplot() and mdaplotg() were rewritten completely and now are more easy to use (check tutorial)
• new color scheme 'jet' with jet colors
• new plot type ('d') for density scatter plot
• support for xlas and ylas in plots to rotate axis ticks
• support for several data attributes to give extra functionality for plots (including manual x-values for line plots)
• rows and columns can be now hidden/excluded via attributes
• factor columns of data frames are now converted to dummy variables automatically when model is created/applied
• scores and loadings plots show % of explained variance in axis labels
• biplot is now available for PCA models (plotBiplot())
• scores plot for PCA model can be now also shown with color grouping (cgroup) if no there is no test set
• cross-validation in PCA and PLS has been improved to make it faster
• added a posibility to exclude selected rows and columns from calculations
• added support for images (check tutorial)

v. 0.7.1

• fixed an issue lead to plot.new() error in some cases
• documentation was regenerated with new version of Roxygen
• file People.RData was renamed to people.RData
• NIPALS method for PCA has been added
• code optimization to speed calculations up

thanks to @zeehio for help.