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

Function to perform a multiblock Partial Least Squares (PLS) of several explanatory blocks *(X_1, …, X_K)* defined as an object of class `ktab`

(from `ade4`

), to explain a dependent dataset *Y* defined as an object of class `dudi`

(from `ade4`

). This function is based on the same code and gives the same results as the `mbpls`

function from the `ade4`

package with additional ones developed for the clusterwise procedure.

1 | ```
mbpls.fast(dudiY, ktabX, scale = FALSE, option = c("none", "uniform"), H)
``` |

`dudiY` |
an object of class |

`ktabX` |
an object of class |

`scale` |
a logical value indicating whether the explanatory variables should be standardized |

`option` |
an option for the block weighting (by default, the first option is chosen): |

`H` |
an integer giving the number of dimensions |

A list containing the following components is returned:

`crit.reg` |
the regression error |

`lX` |
a matrix of the global components associated with the whole explanatory dataset (scores of the individuals) |

`XYcoef` |
a list of matrices of the regression coefficients of the whole explanatory dataset onto the dependent dataset |

`intercept` |
a list of matrices of the regression intercepts of the whole explanatory dataset onto the dependent dataset |

`fitted` |
a list of matrices which contain the predicted dependent values |

Stephanie Bougeard (stephanie.bougeard@anses.fr)

Bougeard, S., Qannari, E.M., Lupo, C. and Hanafi, M. (2011). From multiblock partial least squares to multiblock redundancy analysis. A continuum approach. Informatica, 22(1), 11-26

`cw.multiblock`

, `cw.tenfold`

, `cw.predict`

, `mbpls`

1 2 3 4 5 6 7 8 | ```
data(simdata.red)
Data.X <- simdata.red[c(1:15, 21:35), 1:10]
Data.Y <- simdata.red[c(1:15, 21:35), 11:13]
library(ade4)
dudiy <- dudi.pca(df = Data.Y, center = FALSE, scale = FALSE, scannf = FALSE)
ktabx <- ktab.data.frame(df = data.frame(Data.X), blocks = c(5,5),
tabnames = paste("Tab", c(1:2), sep = "."))
res <- mbpls.fast(dudiy, ktabx, scale = FALSE, option = "none", H = 2)
``` |

```
Loading required package: ade4
Loading required package: doParallel
Loading required package: foreach
Loading required package: iterators
Loading required package: parallel
Loading required package: kknn
Warning messages:
1: In res$lX[, h]/sqrt(t(res$lX[, h]) %*% res$lX[, h]) :
Recycling array of length 1 in vector-array arithmetic is deprecated.
Use c() or as.vector() instead.
2: In res$lX[, h]/sqrt(t(res$lX[, h]) %*% res$lX[, h]) :
Recycling array of length 1 in vector-array arithmetic is deprecated.
Use c() or as.vector() instead.
```

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