Normal plot of effects from a two level factorial experiment.

1 2 3 |

`fit` |
object of class |

`code` |
logical. If |

`faclab` |
list. If |

`block` |
logical. If |

`datax` |
logical. If |

`half` |
logical. If |

`pch` |
numeric or character. Points character. |

`cex.fac` |
numeric. Factors' labels character size. |

`cex.lab` |
numeric. Labels character size. |

`cex.pch` |
numeric. Points character size. |

`...` |
graphical parameters passed to |

The two levels design are assumed -1 and 1. Factor effects assumed `2*coef(obj)`

((Intercept) removed) are displayed in a `qqnorm`

plot with the effects in
the x-axis by default. If `half=TRUE`

the half-normal plots of effects is
plotted as the normal quantiles of `0.5*(rank(abs(effects))-0.5)/length(effects)+1`

versus `abs(effects)`

.

The function returns invisible data frame with columns: `x`

, `y`

and `no`

, for the coordinates and the enumeration of plotted points.
Names of the factor effects (coefficients) are the row names of the data frame.

Ernesto Barrios.

C. Daniel (1976).
*Application of Statistics to Industrial Experimentation.*
Wiley.

Box G. E. P, Hunter, W. C. and Hunter, J. S. (1978).
*Statistics for Experimenters*.
Wiley.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
### Injection Molding Experiment. Box et al. 1978.
library(BsMD)
# Data
data(BM86.data,package="BsMD") # Design matrix and response
print(BM86.data) # from Box and Meyer (1986)
# Model Fitting. Box and Meyer (1986) example 3.
injectionMolding.lm <- lm(y3 ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9 +
X10 + X11 + X12 + X13 + X14 + X15, data = BM86.data)
print(coef(injectionMolding.lm)) # Model coefficients
# Daniel Plots
par(mfrow=c(1,3),oma=c(0,0,1,0),pty="s")
DanielPlot(injectionMolding.lm, half = TRUE, main = "Half-Normal Plot")
DanielPlot(injectionMolding.lm, main = "Normal Plot of Effects")
DanielPlot(injectionMolding.lm,
faclab = list(idx = c(12,4,13), lab = c(" -H"," VG"," -B")),
main = "Active Contrasts")
``` |

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