plot.classes: Graphical representation of regression model outputs

In fsemipar: Estimation, Variable Selection and Prediction for Functional Semiparametric Models

Graphical representation of regression model outputs

Description

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.

Usage

## S3 method for class 'FASSMR.kernel'
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0,...)

## S3 method for class 'FASSMR.kNN'
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)

## S3 method for class 'fsim.kernel'
plot(x,size=15,col1=1,col2=2, ...)

## S3 method for class 'fsim.kNN'
plot(x,size=15,col1=1,col2=2,...)

## S3 method for class 'IASSMR.kernel'
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)

## S3 method for class 'IASSMR.kNN'
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)

## S3 method for class 'lm.pels'
plot(x,size=15,col1=1,col2=2,col3=4, ...)

## S3 method for class 'PVS'
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)

## S3 method for class 'PVS.kernel'
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)

## S3 method for class 'PVS.kNN'
plot(x,ind=1:10, size=15,col1=1,col2=2,col3=4,option=0, ...)

## S3 method for class 'sfpl.kernel'
plot(x,size=15,col1=1,col2=2,col3=4, ...)

## S3 method for class 'sfpl.kNN'
plot(x,size=15,col1=1,col2=2,col3=4, ...)

## S3 method for class 'sfplsim.kernel'
plot(x,size=15,col1=1,col2=2,col3=4, ...)

## S3 method for class 'sfplsim.kNN'
plot(x,size=15,col1=1,col2=2,col3=4, ...)

Arguments

x	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).
ind	Indexes of the colors for the curves in the chart of estimated impact points. The default is 1:10
size	The size for title and axis labels in pts. The default is 15.
col1	Color of the points in the charts. Also, color of the estimated functional index representation. The default is black.
col2	Color of the nonparametric fit representation in FSIM functions, and of the straight line in 'Response vs Fitted Values' charts. The default is red.
col3	Color of the nonparametric fit of the residuals in 'Residuals vs Fitted Values' charts. The default is blue.
option	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.

Value

The functions return different graphical representations.

• For the classes fsim.kNN and fsim.kernel:

  1. The estimated functional index: \hat{\theta}.

  2. The regression fit.

• For the classes lm.pels, sfpl.kernel and sfpl.kNN:

  1. The response over the fitted.values.

  2. The residuals over the fitted.values.

• For the classes sfplsim.kernel and sfplsim.kNN:

  1. The estimated functional index: \hat{\theta}.

  2. The response over the fitted.values.

  3. The residuals over the fitted.values.

• For the classes FASSMR.kernel, FASSMR.kNN, IASSMR.kernel, IASSMR.kNN, sfplsim.kernel and sfplsim.kNN:

  1. If option=1: The curves with the estimated impact points (in dashed vertical lines).

  2. If option=2: The estimated functional index: \hat{\theta}.

  3. If option=3:

     • The response over the fitted.values.

     • The residuals over the fitted.values.

  4. If option=0: All chart are plotted.

• For the classes PVS, PVS.kNN, PVS.kernel:

  1. If option=1: The curves with the estimated impact points (in dashed vertical lines).

  2. If option=2:

     • The response over the fitted.values.

     • The residuals over the fitted.values.

  3. 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.

Author(s)

German Aneiros Perez [e-mail]

Silvia Novo Diaz [e-mail]

See Also

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.

fsemipar documentation built on May 29, 2024, 1:31 a.m.