Displaying 4 results from an estimated 4 matches for "cotabplot".
2009 May 21
1
vcd package --- change layout of plot
...ities ranked them.
The following code (1) works, but the side-by-side plots for Cities PX,
SF are shrunk too much. Stacking PX on top of SF would make for a
better plot. (I could switch the order of Feature and Rank dimensions,
and go with the default side-by-side, but would prefer not to).
(1)
cotabplot(~ Rank + Feature| Cities, data = Pack.dat, gp = shading_max,
rot_labels = c(90, 0, 0, 0),just_labels = c("left", "left",
"left", "right"),set_varnames = c(Feature = ""))
Reading the vcd help, I got lost trying to understand the
panel-generating pa...
2005 Oct 20
0
vcd package 0.9-5 released
...ntroductory vignette on the strucplot framework (including
mosaic, association and sieve plots)
- special vignettes on using/extending shading and labeling functions
* New function spine() for spinograms and spine plots
* New function cd_plot() for conditional density plots
* New function cotabplot() for visualizing conditional independence in a
trellis-like layout, providing panel functions for association,
mosaic, and sieve plots
* Sieve plots are now integrated in the strucplot framework, sieve()
replaces sieveplot()
* Extended support for 'structable' objects (textual repr...
2005 Oct 20
0
vcd package 0.9-5 released
...ntroductory vignette on the strucplot framework (including
mosaic, association and sieve plots)
- special vignettes on using/extending shading and labeling functions
* New function spine() for spinograms and spine plots
* New function cd_plot() for conditional density plots
* New function cotabplot() for visualizing conditional independence in a
trellis-like layout, providing panel functions for association,
mosaic, and sieve plots
* Sieve plots are now integrated in the strucplot framework, sieve()
replaces sieveplot()
* Extended support for 'structable' objects (textual repr...
2010 Mar 24
2
Mosaic
Hi,
I have this data set:
obitoss = c(
5.8,17.4,5.9,17.6,5.8,17.5,4.7,15.8,
3.8,13.4,3.8,13.5,3.7,13.4,3.4,13.6,
4.4,17.3,4.3,17.4,4.2,17.5,4.3,17.0,
4.4,13.6,5.1,14.6,5.7,13.5,3.6,13.3,
6.5,19.6,6.4,19.4,6.3,19.5,6.0,19.7)
(dados = data.frame(
regiao = factor(rep(c('Norte', 'Nordeste', 'Sudeste', 'Sul',
'Centro-Oeste'), each=8)),
ano =