funplot: Plot functional data with linear interpolation of missing...

In FDboost: Boosting Functional Regression Models

Description

Plot functional data with linear interpolation of missing values

Usage

funplot(x, y, id = NULL, rug = TRUE, ...)

Arguments

x	optional, time-vector for plotting
y	matrix of functional data with functions in rows and measured times in columns; or vector or functional observations, in this case id has to be specified
id	defaults to NULL for y matrix, is id-variables for y in long format
rug	logical. Should rugs be plotted? Defaults to TRUE.
...	further arguments passed to matplot.

Details

All observations are marked by a small cross (pch=3). Missing values are imputed by linear interpolation. Parts that are interpolated are plotted by dotted lines, parts with non-missing values as solid lines.

Examples

## Not run: 
### examples for regular data in wide format
data(viscosity)
with(viscosity, funplot(timeAll, visAll, pch=20))
if(require(fda)){
  with(fda::growth, funplot(age, t(hgtm)))
}

## End(Not run)

Example output

Loading required package: mboost
Loading required package: parallel
Loading required package: stabs
This is mboost 2.9-1. See 'package?mboost' and 'news(package  = "mboost")'
for a complete list of changes.

This is FDboost 0.3-2. 
Loading required package: fda
Loading required package: splines
Loading required package: Matrix

Attaching package: 'fda'

The following object is masked from 'package:graphics':

    matplot

FDboost documentation built on May 2, 2019, 6:48 p.m.