Description Usage Arguments Value References Examples

A DISCO-SCA procedure for identifying common and distinctive components.

1 | ```
DISCOsca(DATA, R, Jk)
``` |

`DATA` |
A matrix, which contains the concatenated data with the same subjects from multiple blocks. Note that each row represents a subject. |

`R` |
Number of components (R>=2). |

`Jk` |
A vector containing number of variables in the concatenated data matrix. |

`Trot_best` |
Estimated component score matrix (i.e., T) |

`Prot_best` |
Estimated component loading matrix (i.e., P) |

`comdist` |
A matrix representing common distinctive components. (Rows are data blocks and columns are components.) 0 in the matrix indicating that the corresponding
component of that block is estimated to be zeros, and 1 indicates that (at least one component loading in) the corresponding component of that block is not zero.
Thus, if a column in the |

`propExp_component` |
Proportion of variance per component. |

Schouteden, M., Van Deun, K., Wilderjans, T. F., & Van Mechelen, I. (2014). Performing DISCO-SCA to search for distinctive and common information in linked data. Behavior research methods, 46(2), 576-587.

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