Description Usage Arguments Details Value Author(s) References See Also Examples

Achieves a Correspondence Analysis (CA) on a numeric table of class data.frame

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`x` |
data.frame minimal dimension 4 x 3. The first column |

`nfac` |
Number of factors to retain (maximum 7) |

`isup` |
list of illustrative rows. 0 = no illustrative rows (default) |

`jsup` |
List of illustrative columns. Same as isup. |

`histev` |
Boolean : whether to plot or not the histogram of eigenvalues. |

`grr` |
Boolean : plot the graph of rows on the axes defined by grlist. |

`grc` |
Boolean : Plot the graph of columns on the axes defined by grlist. |

`grrc` |
Boolean : Plot the simultaneous graph of rows and columns on the axes defined by grlist. Labels of rows in black, labels of columns in red. |

`grlist` |
matrix: defines the factorial plans to plot. See details for an example. |

`prtm` |
Boolean: Print or not the data frame. Default = FALSE |

`prtevr` |
Boolean: Print or not the rows eigenvectors. Default = FALSE |

`prtevc` |
Boolean: Print or not the columns eigenvectors. Default = FALSE |

`eps` |
numeric: (tolerance) Precision for null eigenvalues. Default = 10E-09 |

**grlist:** the successive plots to draw are defined by a matrix of dimension k,2. k = number of plans to plot. Example: to plot the plans 1-2, 1-3 and 2-3 enter sometning as matrix(1,2,1,3,2,3,nrow=3,ncol=2,byrow=2) or rbind(c(1,2),c(1,3),c(2,3)).
**Markovian matrix:** In the case of a Markovian or of a transition matrix, one can symetrise (X + t(X)) and load it (sum of the margins added to the diagonal, before applying CA (cf `See Also`

).

In the case of a markovian square matrix (succession or transition matrix) one can symmetrize and load it (`symet`

) before representing it by a graph (`flux`

)

An object of class ca with attributes

`fr ` |
data.frame: weight and factorial coordinates of each row (principal and illustrative). The attribute |

`fc ` |
data.frame: weight and factorial coordinates of each column (principal and illustrative). |

Jean-Sebastien Pierre Jean-sebastien.pierre@univ-rennes1.fr

Van der Heijden, P. G. M. 1986. Transition matrices, model fitting and correspondence analysis. In: Data Analysis and Informatics IV (Ed. by E. Diday), pp. 221-226. Elsevier Science Publishers.

`princomp`

, `compseq`

to build a transition matrix,

`symet`

to modify it (symmetrization and diagonal loading), `flux`

for the design of a graph.

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sequence documentation built on March 26, 2020, 7:30 p.m.

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