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NEWS.md

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FactoMineR2 0.4.0

  • Add all necessary functions to perform Correspondence Analysis (CA) (#9)

  • Replace standardize() and standardize_norm() by pca_standardize() and pca_standardize_norm()

  • Replace get_eig() and get_weighted_eigen() by pca_eigen() and pca_weighted_eigen()

  • Update all unit tests for better testing and coverage

  • Update _pkgdown.yml

  • facto_pca was updated to return same outputs as FactoMineR::PCA()

  • Update CONTRIBUTING.md with coverage testing

FactoMineR2 0.3.0

  • Add facto_mfa() function to perform Multiple Factor Analysis (MFA) (#7)

  • Update unit tests for better testing and coverage

  • Update _pkgdown.yml

FactoMineR2 0.2.1

  • get_weighted_eigen() now returns U matrix as expected (#4)

  • pca_ind_coords() & pca_var_coords() return same signs of the corresponding coordinates as FactoMineR.

  • facto_pca() has been updated. Now, it returns the same output as FactoMineR::PCA().

FactoMineR2 0.2.0

  • facto_pca() is a wrapper function that mimics FactoMineR::PCA().

  • get_weighted_eigen() calculates the same eigs as FactoMineR, whereas get_eigen() calculates the eigs in the unweighted case.

  • eigvalues() and eigvectors() were deprecated.

  • pca_var_cos2() now works as expected.

  • Comparison.Rmd has been updated allowing to compute either supplementary individual coordinates or supplementary variable coordinates.

FactoMineR2 0.1.1

  • standardize() now works as expected with scale = FALSE (#1)

  • A new argument called weights has been added to get_eigen(), eigvalues() and eigvectors() functions. This argument allows to weight the variables in the PCA.

  • standardize_norm() has replaced standardize(type = "norm", ...)

  • Codecov badge has been fixed and now use master instead of main branch for coding coverage.

FactoMineR2 0.1.0

  • get_eig() is a wrapper function that returns eigenvalues and eigenvectors.

  • standardize() is a wrapper function that standardizes the data.

  • pca_ind_*() allows to compute coordinates, cos2 and contribution for active individuals in PCA.

  • pca_var_*() allows to compute coordinates, cos2 and contribution for active variables in PCA.

  • Unit tests were designed for functions mentioned above.

  • Website was built and deployed using pkgdown.