Median polish.

1 2 | ```
## S3 method for class 'matrix'
medianPolish(X, tol=0.01, maxIter=10L, na.rm=NA, ..., .addExtra=TRUE)
``` |

`X` |
N-times-K |

`tol` |
A |

`maxIter` |
Maximum number of iterations. |

`na.rm` |
If |

`.addExtra` |
If |

`...` |
Not used. |

The implementation of this method give identical estimates as
`medpolish`

, but is about 3-5 times more efficient when
there are no `NA`

values.

Returns a named `list`

structure with elements:

`overall` |
The fitted constant term. |

`row` |
The fitted row effect. |

`col` |
The fitted column effect. |

`residuals` |
The residuals. |

`converged` |
If |

Henrik Bengtsson

`medpolish`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
# Deaths from sport parachuting; from ABC of EDA, p.224:
deaths <- matrix(c(14,15,14, 7,4,7, 8,2,10, 15,9,10, 0,2,0), ncol=3, byrow=TRUE)
rownames(deaths) <- c("1-24", "25-74", "75-199", "200++", "NA")
colnames(deaths) <- 1973:1975
print(deaths)
mp <- medianPolish(deaths)
mp1 <- medpolish(deaths, trace=FALSE)
print(mp)
ff <- c("overall", "row", "col", "residuals")
stopifnot(all.equal(mp[ff], mp1[ff]))
# Validate decomposition:
stopifnot(all.equal(deaths, mp$overall+outer(mp$row,mp$col,"+")+mp$resid))
``` |

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