DanielPlot {FrF2} | R Documentation |
The function is modified from the same-name function in packge BsMD with the purpose of providing more usage comfort (correct effect sizes in case of factors, automatic annotation, automatic labelling of the most significant factors only).
DanielPlot(fit, ...) ## S3 method for class 'design': DanielPlot(fit, ..., response = NULL) ## Default S3 method: DanielPlot(fit, code = FALSE, autolab = TRUE, alpha = 0.05, faclab = NULL, block = FALSE, datax = TRUE, half = FALSE, pch = "*", cex.fac = par("cex.lab"), cex.lab = par("cex.lab"), cex.pch = par("cex"), cex.legend = par("cex.lab"), main = NULL, ...)
fit |
an experimental design of class design
with the type element of the design.info attribute
containing “FrF2” or “pb”OR object of class lm . Fitted model from lm or aov . |
... |
further arguments to be passed to the default function,
or graphical parameters to be passed to plot . |
response |
NULL or a character string that specifies response variable to be used,
must be an element of response.names(obj) ;
if NULL, the first response from response.names(obj) is used |
code |
logical. If TRUE labels “A”,“B”, etc. are used
instead of the names of the coefficients (factors). A legend linking
codes to names is provided. |
autolab |
If TRUE, only the significant factors according to the Lenth method
(significance level given by alpha ) are labelled. |
alpha |
significanc level for the Lenth method |
faclab |
NULL or list.
If NULL , point labels are automatically determined according to the
setting of code (i.e. A,B,C etc. for code=TRUE , natural effect
names otherwise) and autolab (i.e. all effects are labelled if autolab=FALSE ,
only significant effects are labelled if autolab=TRUE ).
Otherwise, faclab can be used for manual labelling of certain effects
and should be a list with idx (integer vector referring to
position of effects to be labelled) and lab (character vector of labels)
components.
|
block |
logical. If TRUE , the first factor is labelled as “BK” (block). |
datax |
logical. If TRUE , the x-axis is used for the factor effects the
the y-axis for the normal scores. The opposite otherwise. |
half |
logical. If TRUE , half-normal plot of effects is display. |
pch |
numeric or character. Points character. |
cex.fac |
numeric. Factor label character size. |
cex.lab |
numeric. Labels character size. |
cex.pch |
numeric. Points character size. |
cex.legend |
numeric. Legend size in case of codes. |
main |
NULL or character. Title of plot. If NULL, automatic title is generated. |
The design underlying fit
has to be a (regular or non-regular) fractional factorial 2-level design.
Effects (except for the intercept) are displayed in a normal or half-normal
plot with the effects in the x-axis by default.
If fit
is a design with at least one response variable
rather than a linear model fit,
the lm
-method for class design
is applied to it with
degree high enough that at least one effect is assigned to each column of the Yates matrix,
and the default method for DanielPlot
is afterwards applied to the
resulting linear model.
The function returns an invisible data frame with columns: x
, y
,
no
and effect
, for the coordinates, the position numbers and
the effect names for plotted points.
Ernesto Barrios, modified by Ulrike Groemping.
Box G. E. P, Hunter, W. C. and Hunter, J. S. (2005) Statistics for Experimenters, 2nd edition. New York: Wiley.
Daniel, C. (1959) Use of Half Normal Plots in Interpreting Two Level Experiments. Technometrics 1, 311–340.
Daniel, C. (1976) Application of Statistics to Industrial Experimentation. New York: Wiley.
Lenth, R.V. (1989) Quick and easy analysis of unreplicated factorials. Technometrics 31, 469–473.
Lenth, R.V. (2006) Lenth s Method for the Analysis of Unreplicated Experiments. To appear in Encyclopedia of Statistics in Quality and Reliability, Wiley, New York. Downloadable at http://www.wiley.com/legacy/wileychi/eqr/docs/sample_1.pdf.
qqnorm
, LenthPlot
, BsMD-package