VERSION 1.1.0
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   o Added guidedPCA() function for guided principal component analysis
   o guidedPCA() automatically handles mixed data types (continuous, categorical, logical)
   o Added automatic dummy variable encoding for categorical variables
   o Added feature contribution analysis to identify important features per component
   o Added variance explained calculation for each component
   o Added print() and summary() methods for guidedPCA objects
   o Added comprehensive unit tests for guidedPCA()
   o Updated package documentation with detailed algorithm descriptions
   o Added 'stats' to Imports for better dependency management

   VERSION 1.0.0
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   o Added cortest in PLSSVD() and sPLSDA()

   VERSION 0.99.0
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   o Package released