plot functions to generate visual representations for the outputs of several fitting functions: FASSMR.kernel.fit, FASSMR.kNN.fit, fsim.kernel.fit, fsim.kernel.fit.optim, fsim.kNN.fit, fsim.kNN.fit.optim, IASSMR.kernel.fit, IASSMR.kNN.fit, lm.pels.fit, PVS.fit, PVS.kernel.fit, PVS.kNN.fit, sfpl.kernel.fit, sfpl.kNN.fit,sfplsim.kernel.fit and sfplsim.kNN.fit.
# S3 method for FASSMR.kernel
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0,...)# S3 method for FASSMR.kNN
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)
# S3 method for fsim.kernel
plot(x,size=15,col1=1,col2=2, ...)
# S3 method for fsim.kNN
plot(x,size=15,col1=1,col2=2,...)
# S3 method for IASSMR.kernel
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)
# S3 method for IASSMR.kNN
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)
# S3 method for lm.pels
plot(x,size=15,col1=1,col2=2,col3=4, ...)
# S3 method for PVS
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)
# S3 method for PVS.kernel
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)
# S3 method for PVS.kNN
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)
# S3 method for sfpl.kernel
plot(x,size=15,col1=1,col2=2,col3=4, ...)
# S3 method for sfpl.kNN
plot(x,size=15,col1=1,col2=2,col3=4, ...)
# S3 method for sfplsim.kernel
plot(x,size=15,col1=1,col2=2,col3=4, ...)
# S3 method for sfplsim.kNN
plot(x,size=15,col1=1,col2=2,col3=4, ...)
The functions return different graphical representations.
For the classes fsim.kNN and fsim.kernel:
The estimated functional index: \(\hat{\theta}\).
The regression fit.
For the classes lm.pels, sfpl.kernel and sfpl.kNN:
The response over the fitted.values.
The residuals over the fitted.values.
For the classes sfplsim.kernel and sfplsim.kNN:
The estimated functional index: \(\hat{\theta}\).
The response over the fitted.values.
The residuals over the fitted.values.
For the classes FASSMR.kernel, FASSMR.kNN, IASSMR.kernel, IASSMR.kNN, sfplsim.kernel and sfplsim.kNN:
If option=1: The curves with the estimated impact points (in dashed vertical lines).
If option=2: The estimated functional index: \(\hat{\theta}\).
If option=3:
The response over the fitted.values.
The residuals over the fitted.values.
If option=0: All chart are plotted.
For the classes PVS, PVS.kNN, PVS.kernel:
If option=1: The curves with the estimated impact points (in dashed vertical lines).
If option=2:
The response over the fitted.values.
The residuals over the fitted.values.
If option=0: All chart are plotted.
All the routines implementing the plot S3 method use internally the R package ggplot2 to produce elegant and high quality
charts.
Output of the functions mentioned in the Description (i.e. an object of the class FASSMR.kernel, FASSMR.kNN, fsim.kernel,fsim.kNN, IASSMR.kernel, IASSMR.kNN, lm.pels, PVS, PVS.kernel, PVS.kNN, sfpl.kernel,sfpl.kNN, sfplsim.kernel or sfplsim.kNN).
Indexes of the colors for the curves in the chart of estimated impact points. The default is 1:10
The size for title and axis labels in pts. The default is 15.
Color of the points in the charts. Also, color of the estimated functional index representation. The default is black.
Color of the nonparametric fit representation in FSIM functions, and of the straight line in 'Response vs Fitted Values' charts. The default is red.
Color of the nonparametric fit of the residuals in 'Residuals vs Fitted Values' charts. The default is blue.
Selection of charts to be plotted. The default, option = 0, means all charts are plotted. See the section Details.
Further arguments passed to or from other methods.
German Aneiros Perez german.aneiros@udc.es
Silvia Novo Diaz snovo@est-econ.uc3m.es
FASSMR.kernel.fit, FASSMR.kNN.fit, fsim.kernel.fit, fsim.kNN.fit, IASSMR.kernel.fit, IASSMR.kNN.fit, lm.pels.fit, PVS.fit, PVS.kernel.fit, PVS.kNN.fit, sfpl.kernel.fit, sfpl.kNN.fit, sfplsim.kernel.fit and sfplsim.kNN.fit.