Two subsets of data each take in turn the role of test set

Returns on aov F-statistic for each row of `x`

1 |

`x` |
features by observations matrix |

`cl` |
factor that classifies the values in each row |

This uses the functions `qr()`

and `qr.qty()`

for the main
part of the calculation, for handling the calculations efficently

one F-statistic for each row of `x`

John Maindonald

See also `orderFeatures`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
mat <- matrix(rnorm(1000), ncol=20)
cl <- factor(rep(1:3, c(7,9,4)))
Fstats <- aovFbyrow(x = mat, cl = cl)
## The function is currently defined as
aovFbyrow <-
function(x=matrix(rnorm(1000), ncol=20),
cl=factor(rep(1:3, c(7,9,4)))){
y <- t(x)
qr.obj <- qr(model.matrix(~cl))
qty.obj <- qr.qty(qr.obj,y)
tab <- table(factor(cl))
dfb <- length(tab)-1
dfw <- sum(tab)-dfb-1
ms.between <- apply(qty.obj[2:(dfb+1), , drop=FALSE]^2, 2, sum)/dfb
ms.within <- apply(qty.obj[-(1:(dfb+1)), , drop=FALSE]^2, 2, sum)/dfw
Fstat <- ms.between/ms.within
}
``` |

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