trans.plot {pda} | R Documentation |
Diagnostic plot to find power transform to remove
interaction. See Emerson chapter in Hoaglin, Mosteller and Tukey
(1991, ch. 13E) Fundamentals of Exploratory Analysis of Variance
(Wiley);or see Mosteller and Tukey (1977, ch. 9E,F) Exploratory Data
Analysis (Addison-Wesley).
Description
Usage
trans.plot(fit, predictors=all.predictors(fit)[1:2],
terms=predict(fit, type = "terms"), xlab, ylab, ...)
Arguments
fit |
linear model (lm) fit |
predictors |
predictors to compare. They must be in the model, as
well as theirinteraction in the specified order. |
terms |
estimates of model terms |
xlab,ylab |
x and y axis labels |
... |
Plot parameters |
Value
Power = 1 - slope estimate. SE comes from simple linear
regression and is at best advisory. Consider tranformation $y^p$ =
exp(p*log(y)), or transform log(y) if p=0. In practice, examine
nearest half integer.
See Also
effect.plot
.
Examples
## Not run:
# Bekk data from Hoaglin, Mosteller and Tukey (1991)
bekk.fit <- lm(smooth~lab*mat, bekk)
effect.plot(bekk.fit)trans.plot(bekk.fit)
bekk.lfit <- lm(log(smooth)~lab*mat, bekk)
effect.plot(bekk.lfit)
trans.plot(bekk.lfit)
## End(Not run)
[Package
pda version 1.2-7
Index]