Detects the underlying structure of a three-way array according to the Candecomp/Parafac (CP) model.

1 |

`data` |
Array of order |

`laba` |
Optional vector of length |

`labb` |
Optional vector of length |

`labc` |
Optional vector of length |

A list including the following components:

`A` |
Component matrix for the |

`B` |
Component matrix for the |

`C` |
Component matrix for the |

`fit` |
Fit value expressed as a percentage |

`tripcos` |
Matrix of the triple cosines among pairs of components (to inspect degeneracy) |

`fitValues` |
Fit values expressed as a percentage upon convergence for all the runs of the CP algorithm (see |

`funcValues` |
Function values upon convergence for all the runs of the CP algorithm (see |

`cputime` |
Computation times for all the runs of the CP algorithm (see |

`iter` |
Numbers of iterations upon convergence for all the runs of the CP algorithm (see |

`fitA` |
Fit contributions for the |

`fitB` |
Fit contributions for the |

`fitC` |
Fit contributions for the |

`Bint` |
Bootstrap percentile interval of every element of |

`Cint` |
Bootstrap percentile interval of every element of |

`fpint` |
Bootstrap percentile interval for the goodness of fit index expressed as a percentage (see |

`Afull` |
Component matrix for the |

`As1` |
Component matrix for the |

`As2` |
Component matrix for the |

`Bfull` |
Component matrix for the |

`Bs1` |
Component matrix for the |

`Bs2` |
Component matrix for the |

`Cfull` |
Component matrix for the |

`Cs1` |
Component matrix for the |

`Cs2` |
Component matrix for the |

`A1` |
Component matrix for the |

`B1` |
Component matrix for the |

`C1` |
Component matrix for the |

`A2` |
Component matrix for the |

`B2` |
Component matrix for the |

`C2` |
Component matrix for the |

`laba` |
Vector of length |

`labb` |
Vector of length |

`labc` |
Vector of length |

`Xprep` |
Matrix of order ( |

Maria Antonietta Del Ferraro mariaantonietta.delferraro@yahoo.it

Henk A.L. Kiers h.a.l.kiers@rug.nl

Paolo Giordani paolo.giordani@uniroma1.it

J.D. Carroll and J.J. Chang (1970). Analysis of individual differences in multidimensional scaling via an *N*-way generalization of 'Eckart-Young' decomposition. *Psychometrika 35:283–319*.

P. Giordani, H.A.L. Kiers, M.A. Del Ferraro (2014). Three-way component analysis using the R package ThreeWay. *Journal of Statistical Software 57(7):1–23*. http://www.jstatsoft.org/v57/i07/.

R.A. Harshman (1970). Foundations of the Parafac procedure: models and conditions for an 'explanatory' multi-mode factor analysis. *UCLA Working Papers in Phonetics 16:1–84*.

P.M. Kroonenberg (2008). *Applied Multiway Data Analysis*. Wiley, New Jersey.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
data(TV)
TVdata=TV[[1]]
labSCALE=TV[[2]]
labPROGRAM=TV[[3]]
labSTUDENT=TV[[4]]
# permutation of the modes so that the A-mode refers to students
TVdata <- permnew(TVdata, 16, 15, 30)
TVdata <- permnew(TVdata, 15, 30, 16)
## Not run:
# interactive CP analysis
TVcp <- CP(TVdata, labSTUDENT, labSCALE, labPROGRAM)
# interactive CP analysis (when labels are not available)
TVcp <- CP(TVdata)
## End(Not run)
``` |

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