plot.nominal.logistic.biplot: Graphical representation of a Nominal Logistic Biplot.
In NominalLogisticBiplot: Biplot representations of categorical data
Description
Usage
Arguments
Details
Author(s)
See Also
Examples
View source: R/NominalLogisticBiplot.R
Description
Plotting a Nominal Logistic Biplot. There are parameters related to the way in which the biplot is plotted. All the posible parameters have default values
Usage
1
2
3
4
5
6
7
8
9
10
## S3 method for class 'nominal.logistic.biplot'
## S3 method for class 'nominal.logistic.biplot'
plot(x, planex = 1, planey = 2,
QuitNotPredicted = TRUE, ReestimateInFocusPlane = TRUE,
proofMode = FALSE, AtLeastR2 = 0.01, xlimi = -1.5, xlimu = 1.5,
ylimi = -1.5, ylimu = 1.5, linesVoronoi = FALSE, ShowAxis = TRUE,
PlotVars = TRUE, PlotInd = TRUE, LabelVar = TRUE, LabelInd = TRUE,
CexInd = NULL, CexVar = NULL, ColorInd = NULL, ColorVar = NULL,
SmartLabels = FALSE, PchInd = NULL, PchVar = NULL,
LabelValuesVar = NULL, ShowResults = FALSE,...)
Arguments
x
An object of the class nominal.logistic.biplot.
planex
Dimension for X axis.
planey
Dimension for Y axis.
QuitNotPredicted
Should the non-predicted categories be represented on the graph?
ReestimateInFocusPlane
Shuld the item parameters be reestimated using only the dimensiona of the plot.? If FALSE the values of the parameters for other dimensions are set to 0. Default is FALSE
proofMode
Should each variable be plotted on a separate plot? If FALSE, a single plot with a legend for identifying each variable is made.
AtLeastR2
It establishes the cutting value to plot a variable attending to its Nagelkerke R^2 value. A variable is plotted if its R^2 is higher than this value.
xlimi
Minimum value on the x-axis.
xlimu
Maximum value on the x-axis.
ylimi
Minimum value on the y-axis.
ylimu
Maximum value on the y-axis.
linesVoronoi
Should the tesselation be plotted.? Default is FALSE and only the category points are plotted for a better reading of the plot.
ShowAxis
Should the axis be shown?
PlotVars
Should the variables (items) be pplotted?
PlotInd
Should the individuals be plotted?
LabelVar
Should the variable labels be shown?
LabelInd
Should the individual labels be shown?
CexInd
Size of the individual points. It can be an array with the cex information for each row.
CexVar
Size of the category points. It can be an array with the cex information for each variable.
ColorInd
Color of the individual points. It can be an array with the color information for each row.
ColorVar
Color for the variables. It can be an array with the color information for each variable.
SmartLabels
Should the text labels be printed accordind to its position on the plot?.
PchInd
Symbol for the individuals. It can be an array with the pch information for each row.
PchVar
Symbol for the variables. It could be an array with the pch information for each variable.
LabelValuesVar
List with the text labels for all the variables. If NULL, initial labels are used.
ShowResults
Should the results of the proccess of calculating the prediction regions be shown?
...
Additional parameters to plot.
Details
The function without parameters plots the nominal.logistic.biplot object with labels in the original data and default values for colors, symbols and sizes for points and lines. Other values of colors, symbols and sizes can be supplied. A single value applies to all the points but an array with different values can be used to improve the undestanding of the plot.-
Author(s)
Julio Cesar Hernandez Sanchez, Jose Luis Vicente-Villardon
Maintainer: Julio Cesar Hernandez Sanchez <juliocesar_avila@usal.es>
See Also
Examples
1
2
3
4
5
6
7
8
9
10
11
12
data(HairColor)
nlbo = NominalLogisticBiplot(HairColor,sFormula=NULL,
numFactors=2,method="EM",penalization=0.2,show=FALSE)
plot(nlbo,QuitNotPredicted=TRUE,ReestimateInFocusPlane=TRUE,
planex = 1,planey = 2,proofMode=TRUE,LabelInd=TRUE,
AtLeastR2 = 0.01,xlimi=-1.5,xlimu=1.5,ylimi=-1.5,
ylimu=1.5,linesVoronoi = TRUE,SmartLabels = FALSE,
PlotInd=TRUE,CexInd = c(0.6,0.7,0.5,0.4,0.5,0.6,0.7)
,PchInd = c(1,2,3,4,5,6,7),ColorInd="black",PlotVars=TRUE,
LabelVar = TRUE,PchVar = c(1,2,3,4,5),
ColorVar = c("red","black","yellow","blue","green")
,ShowResults=TRUE)
Example output
Loading required package: mirt
Loading required package: stats4
Loading required package: lattice
Loading required package: gmodels
Loading required package: MASS
[1] "Iteration 11- Log-Lik:-19.8216048520061 - Change:8.84634074071008e-05"
[1] "Iteracion.Variable l=1"
[1] "Iteracion.Variable l=2"
[1] "Iteracion.Variable l=3"
[1] "Iteracion.Variable l=4"
[1] "Iteracion.Variable l=5"
[1] "Fitting adjustment for the variables"
Sex HairColor Region Work Education
PCC 71.43 100.00 85.71 100.00 100.00
CoxSnell 0.31 0.69 0.53 0.70 0.69
Macfaden 0.27 0.45 0.35 0.55 0.58
Nagelkerke 0.41 0.75 0.59 0.79 0.79
[1] "Coordinates of the rows for the plane:1-2\n"
[,1] [,2]
George -0.6559734 0.3181114
Alisdair 0.7243489 -0.7750341
Jane 0.4540670 -0.1668629
Ivor 0.6753478 0.4890209
Myfanwy -0.7240033 -0.7850541
Harriet -0.8912034 0.1142096
Jeremy 0.1254554 1.1062286
[1] "Variable:Sex"
[1] "PCC:71.43"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] -0.2627523 -0.9437358 -0.9465762
[1] "Pseudo R2 Nagelkerke:0.409403623865819"
[1] "Tesselation information:"
[1] 0
[1] "-----------------"
[1] "Variable:HairColor"
[1] "PCC:100"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] -0.7095129 0.9966865 -0.9259602
[2,] -0.8167778 -0.4979981 -1.0374218
[3,] -0.3835626 1.0419528 1.3953696
[1] "Pseudo R2 Nagelkerke:0.745594557043983"
[1] "Tesselation information:"
$x
[1] -0.01353718 0.57107462
$y
[1] -0.7808168 -0.1515514
$node
[1] TRUE TRUE
$n1
[1] -1 -3
$n2
[1] -2 -4
$n3
[1] 2 1
$dummy.x
[1] -12.0029455 0.1299986 -9.6644983 2.4684458
$dummy.y
[1] 4.9745116 -2.7056120 7.4915732 -0.1885504
$ndummy
[1] 4
$IndReal
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 4
$Centers
[,1] [,2]
[1,] -0.1622435 -0.3004050
[2,] 0.4765020 -0.8938242
[3,] -0.4813951 -0.9652565
[4,] 0.5055117 0.5938441
$hideCat
[,1] [,2] [,3] [,4]
[1,] 0 0 0 0
$equivRegiones
[,1] [,2] [,3] [,4]
[1,] 1 2 3 4
[2,] 1 2 3 4
attr(,"class")
[1] "voronoiprob"
[1] "-----------------"
[1] "Variable:Region"
[1] "PCC:85.71"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] -0.2623280 1.4568048 -1.3172196
[2,] -0.1429362 0.4543351 -0.7522487
[1] "Pseudo R2 Nagelkerke:0.594207768759697"
[1] "Tesselation information:"
$x
[1] 0.01820889
$y
[1] -0.1790143
$node
[1] TRUE
$n1
[1] -1
$n2
[1] -2
$n3
[1] -3
$dummy.x
[1] 2.018209 -1.981791 -1.981791
$dummy.y
[1] 2.032925 -1.386953 -3.727763
$ndummy
[1] 3
$IndReal
[,1] [,2] [,3]
[1,] 1 2 3
$Centers
[,1] [,2]
[1,] -0.930579 -0.4949282
[2,] -0.200867 -1.1547222
[3,] -0.703003 -0.8717289
$hideCat
[,1] [,2] [,3]
[1,] 0 0 0
$equivRegiones
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 3
attr(,"class")
[1] "voronoiprob"
[1] "-----------------"
[1] "Variable:Work"
[1] "PCC:100"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] -0.1810928 0.4804015 -1.7006020
[2,] 0.2466705 1.5695526 0.9286689
[1] "Pseudo R2 Nagelkerke:0.786859365555821"
[1] "Tesselation information:"
$x
[1] -0.08067012
$y
[1] -0.1292759
$node
[1] TRUE
$n1
[1] -1
$n2
[1] -2
$n3
[1] -3
$dummy.x
[1] -2.08067 -2.08067 1.91933
$dummy.y
[1] -0.6942541 3.2509441 -0.9577573
$ndummy
[1] 3
$IndReal
[,1] [,2] [,3]
[1,] 1 2 3
$Centers
[,1] [,2]
[1,] -1.01354560 0.2309231
[2,] -0.68719660 -0.9243392
[3,] 0.05269145 0.8617916
$hideCat
[,1] [,2] [,3]
[1,] 0 0 0
$equivRegiones
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 3
attr(,"class")
[1] "voronoiprob"
[1] "-----------------"
[1] "Variable:Education"
[1] "PCC:100"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] 0.1471379 2.099336 -0.3909374
[2,] -0.8238265 0.638930 1.2025888
[1] "Pseudo R2 Nagelkerke:0.793451254440272"
[1] "Tesselation information:"
$x
[1] 0.05230581
$y
[1] 0.6572544
$node
[1] TRUE
$n1
[1] -1
$n2
[1] -2
$n3
[1] -3
$dummy.x
[1] -1.947694 -1.947694 2.052306
$dummy.y
[1] -10.082756 1.719845 2.490178
$ndummy
[1] 3
$IndReal
[,1] [,2] [,3]
[1,] 1 2 3
$Centers
[,1] [,2]
[1,] -0.9354761 0.5014119
[2,] 0.9177792 0.1562995
[3,] -0.3714404 1.5630354
$hideCat
[,1] [,2] [,3]
[1,] 0 0 0
$equivRegiones
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 3
attr(,"class")
[1] "voronoiprob"
[1] "-----------------"
dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")
dev.new(): using pdf(file="Rplots4.pdf")
NominalLogisticBiplot documentation built on May 2, 2019, 6:03 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Details Author(s) See Also Examples
View source: R/NominalLogisticBiplot.R
Description
Plotting a Nominal Logistic Biplot. There are parameters related to the way in which the biplot is plotted. All the posible parameters have default values
Usage
1 2 3 4 5 6 7 8 9 10 | ## S3 method for class 'nominal.logistic.biplot'
## S3 method for class 'nominal.logistic.biplot'
plot(x, planex = 1, planey = 2,
QuitNotPredicted = TRUE, ReestimateInFocusPlane = TRUE,
proofMode = FALSE, AtLeastR2 = 0.01, xlimi = -1.5, xlimu = 1.5,
ylimi = -1.5, ylimu = 1.5, linesVoronoi = FALSE, ShowAxis = TRUE,
PlotVars = TRUE, PlotInd = TRUE, LabelVar = TRUE, LabelInd = TRUE,
CexInd = NULL, CexVar = NULL, ColorInd = NULL, ColorVar = NULL,
SmartLabels = FALSE, PchInd = NULL, PchVar = NULL,
LabelValuesVar = NULL, ShowResults = FALSE,...)
|
Arguments
x |
An object of the class nominal.logistic.biplot. |
planex |
Dimension for X axis. |
planey |
Dimension for Y axis. |
QuitNotPredicted |
Should the non-predicted categories be represented on the graph? |
ReestimateInFocusPlane |
Shuld the item parameters be reestimated using only the dimensiona of the plot.? If FALSE the values of the parameters for other dimensions are set to 0. Default is FALSE |
proofMode |
Should each variable be plotted on a separate plot? If FALSE, a single plot with a legend for identifying each variable is made. |
AtLeastR2 |
It establishes the cutting value to plot a variable attending to its Nagelkerke R^2 value. A variable is plotted if its R^2 is higher than this value. |
xlimi |
Minimum value on the x-axis. |
xlimu |
Maximum value on the x-axis. |
ylimi |
Minimum value on the y-axis. |
ylimu |
Maximum value on the y-axis. |
linesVoronoi |
Should the tesselation be plotted.? Default is FALSE and only the category points are plotted for a better reading of the plot. |
ShowAxis |
Should the axis be shown? |
PlotVars |
Should the variables (items) be pplotted? |
PlotInd |
Should the individuals be plotted? |
LabelVar |
Should the variable labels be shown? |
LabelInd |
Should the individual labels be shown? |
CexInd |
Size of the individual points. It can be an array with the cex information for each row. |
CexVar |
Size of the category points. It can be an array with the cex information for each variable. |
ColorInd |
Color of the individual points. It can be an array with the color information for each row. |
ColorVar |
Color for the variables. It can be an array with the color information for each variable. |
SmartLabels |
Should the text labels be printed accordind to its position on the plot?. |
PchInd |
Symbol for the individuals. It can be an array with the pch information for each row. |
PchVar |
Symbol for the variables. It could be an array with the pch information for each variable. |
LabelValuesVar |
List with the text labels for all the variables. If NULL, initial labels are used. |
ShowResults |
Should the results of the proccess of calculating the prediction regions be shown? |
... |
Additional parameters to plot. |
Details
The function without parameters plots the nominal.logistic.biplot object with labels in the original data and default values for colors, symbols and sizes for points and lines. Other values of colors, symbols and sizes can be supplied. A single value applies to all the points but an array with different values can be used to improve the undestanding of the plot.-
Author(s)
Julio Cesar Hernandez Sanchez, Jose Luis Vicente-Villardon
Maintainer: Julio Cesar Hernandez Sanchez <juliocesar_avila@usal.es>
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 | data(HairColor)
nlbo = NominalLogisticBiplot(HairColor,sFormula=NULL,
numFactors=2,method="EM",penalization=0.2,show=FALSE)
plot(nlbo,QuitNotPredicted=TRUE,ReestimateInFocusPlane=TRUE,
planex = 1,planey = 2,proofMode=TRUE,LabelInd=TRUE,
AtLeastR2 = 0.01,xlimi=-1.5,xlimu=1.5,ylimi=-1.5,
ylimu=1.5,linesVoronoi = TRUE,SmartLabels = FALSE,
PlotInd=TRUE,CexInd = c(0.6,0.7,0.5,0.4,0.5,0.6,0.7)
,PchInd = c(1,2,3,4,5,6,7),ColorInd="black",PlotVars=TRUE,
LabelVar = TRUE,PchVar = c(1,2,3,4,5),
ColorVar = c("red","black","yellow","blue","green")
,ShowResults=TRUE)
|
Example output
Loading required package: mirt
Loading required package: stats4
Loading required package: lattice
Loading required package: gmodels
Loading required package: MASS
[1] "Iteration 11- Log-Lik:-19.8216048520061 - Change:8.84634074071008e-05"
[1] "Iteracion.Variable l=1"
[1] "Iteracion.Variable l=2"
[1] "Iteracion.Variable l=3"
[1] "Iteracion.Variable l=4"
[1] "Iteracion.Variable l=5"
[1] "Fitting adjustment for the variables"
Sex HairColor Region Work Education
PCC 71.43 100.00 85.71 100.00 100.00
CoxSnell 0.31 0.69 0.53 0.70 0.69
Macfaden 0.27 0.45 0.35 0.55 0.58
Nagelkerke 0.41 0.75 0.59 0.79 0.79
[1] "Coordinates of the rows for the plane:1-2\n"
[,1] [,2]
George -0.6559734 0.3181114
Alisdair 0.7243489 -0.7750341
Jane 0.4540670 -0.1668629
Ivor 0.6753478 0.4890209
Myfanwy -0.7240033 -0.7850541
Harriet -0.8912034 0.1142096
Jeremy 0.1254554 1.1062286
[1] "Variable:Sex"
[1] "PCC:71.43"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] -0.2627523 -0.9437358 -0.9465762
[1] "Pseudo R2 Nagelkerke:0.409403623865819"
[1] "Tesselation information:"
[1] 0
[1] "-----------------"
[1] "Variable:HairColor"
[1] "PCC:100"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] -0.7095129 0.9966865 -0.9259602
[2,] -0.8167778 -0.4979981 -1.0374218
[3,] -0.3835626 1.0419528 1.3953696
[1] "Pseudo R2 Nagelkerke:0.745594557043983"
[1] "Tesselation information:"
$x
[1] -0.01353718 0.57107462
$y
[1] -0.7808168 -0.1515514
$node
[1] TRUE TRUE
$n1
[1] -1 -3
$n2
[1] -2 -4
$n3
[1] 2 1
$dummy.x
[1] -12.0029455 0.1299986 -9.6644983 2.4684458
$dummy.y
[1] 4.9745116 -2.7056120 7.4915732 -0.1885504
$ndummy
[1] 4
$IndReal
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 4
$Centers
[,1] [,2]
[1,] -0.1622435 -0.3004050
[2,] 0.4765020 -0.8938242
[3,] -0.4813951 -0.9652565
[4,] 0.5055117 0.5938441
$hideCat
[,1] [,2] [,3] [,4]
[1,] 0 0 0 0
$equivRegiones
[,1] [,2] [,3] [,4]
[1,] 1 2 3 4
[2,] 1 2 3 4
attr(,"class")
[1] "voronoiprob"
[1] "-----------------"
[1] "Variable:Region"
[1] "PCC:85.71"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] -0.2623280 1.4568048 -1.3172196
[2,] -0.1429362 0.4543351 -0.7522487
[1] "Pseudo R2 Nagelkerke:0.594207768759697"
[1] "Tesselation information:"
$x
[1] 0.01820889
$y
[1] -0.1790143
$node
[1] TRUE
$n1
[1] -1
$n2
[1] -2
$n3
[1] -3
$dummy.x
[1] 2.018209 -1.981791 -1.981791
$dummy.y
[1] 2.032925 -1.386953 -3.727763
$ndummy
[1] 3
$IndReal
[,1] [,2] [,3]
[1,] 1 2 3
$Centers
[,1] [,2]
[1,] -0.930579 -0.4949282
[2,] -0.200867 -1.1547222
[3,] -0.703003 -0.8717289
$hideCat
[,1] [,2] [,3]
[1,] 0 0 0
$equivRegiones
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 3
attr(,"class")
[1] "voronoiprob"
[1] "-----------------"
[1] "Variable:Work"
[1] "PCC:100"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] -0.1810928 0.4804015 -1.7006020
[2,] 0.2466705 1.5695526 0.9286689
[1] "Pseudo R2 Nagelkerke:0.786859365555821"
[1] "Tesselation information:"
$x
[1] -0.08067012
$y
[1] -0.1292759
$node
[1] TRUE
$n1
[1] -1
$n2
[1] -2
$n3
[1] -3
$dummy.x
[1] -2.08067 -2.08067 1.91933
$dummy.y
[1] -0.6942541 3.2509441 -0.9577573
$ndummy
[1] 3
$IndReal
[,1] [,2] [,3]
[1,] 1 2 3
$Centers
[,1] [,2]
[1,] -1.01354560 0.2309231
[2,] -0.68719660 -0.9243392
[3,] 0.05269145 0.8617916
$hideCat
[,1] [,2] [,3]
[1,] 0 0 0
$equivRegiones
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 3
attr(,"class")
[1] "voronoiprob"
[1] "-----------------"
[1] "Variable:Education"
[1] "PCC:100"
[1] "Coefficients from adjusted model"
[,1] [,2] [,3]
[1,] 0.1471379 2.099336 -0.3909374
[2,] -0.8238265 0.638930 1.2025888
[1] "Pseudo R2 Nagelkerke:0.793451254440272"
[1] "Tesselation information:"
$x
[1] 0.05230581
$y
[1] 0.6572544
$node
[1] TRUE
$n1
[1] -1
$n2
[1] -2
$n3
[1] -3
$dummy.x
[1] -1.947694 -1.947694 2.052306
$dummy.y
[1] -10.082756 1.719845 2.490178
$ndummy
[1] 3
$IndReal
[,1] [,2] [,3]
[1,] 1 2 3
$Centers
[,1] [,2]
[1,] -0.9354761 0.5014119
[2,] 0.9177792 0.1562995
[3,] -0.3714404 1.5630354
$hideCat
[,1] [,2] [,3]
[1,] 0 0 0
$equivRegiones
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 1 2 3
attr(,"class")
[1] "voronoiprob"
[1] "-----------------"
dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")
dev.new(): using pdf(file="Rplots4.pdf")
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.