R: Create a Polygonal Basis

create.polygonal.basis {fda} | R Documentation

## Create a Polygonal Basis

### Description

A basis is set up for constructing polygonal lines, consisting of straight line segments that join together.

### Usage

    create.polygonal.basis(rangeval=NULL, argvals=NULL, dropind=NULL,
            quadvals=NULL, values=NULL, basisvalues=NULL, names='polygon',
            axes=NULL)

### Arguments

`rangeval` | a numeric vector of length 2 defining the interval over which the functional data object can be evaluated; default value is `if(is.null(argvals)) 0:1 else range(argvals)`. If `length(rangeval) == 1` and `rangeval <= 0`, this is an error. Otherwise, if `length(rangeval) == 1`, `rangeval` is replaced by `c(0,rangeval)`. If length(rangeval)>2 and `argvals` is not provided, this extra long `rangeval` argument is assigned to `argvals`, and then `rangeval = range(argvale)`.
`argvals` | a strictly increasing vector of argument values at which line segments join to form a polygonal line.
`dropind` | a vector of integers specifiying the basis functions to be dropped, if any. For example, if it is required that a function be zero at the left boundary, this is achieved by dropping the first basis function, the only one that is nonzero at that point.
`quadvals` | a matrix with two columns and a number of rows equal to the number of quadrature points for numerical evaluation of the penalty integral. The first column of `quadvals` contains the quadrature points, and the second column the quadrature weights. A minimum of 5 values are required for each inter-knot interval, and that is often enough. For Simpson's rule, these points are equally spaced, and the weights are proportional to These are proportional to 1, 4, 2, 4, ..., 2, 4, 1.
`values` | a list containing the basis functions and their derivatives evaluated at the quadrature points contained in the first column of `quadvals` .
`basisvalues` | A list of lists, allocated by code such as vector("list",1). This is designed to avoid evaluation of a basis system repeatedly at a set of argument values. Each sublist corresponds to a specific set of argument values, and must have at least two components, which may be named as you wish. The first component of a sublist contains the argument values. The second component contains a matrix of values of the basis functions evaluated at the arguments in the first component. The third and subsequent components, if present, contain matrices of values their derivatives up to a maximum derivative order. Whenever function `getbasismatrix` is called, it checks the first list in each row to see, first, if the number of argument values corresponds to the size of the first dimension, and if this test succeeds, checks that all of the argument values match. This takes time, of course, but is much faster than re-evaluation of the basis system. Even this time can be avoided by direct retrieval of the desired array. For example, you might set up a vector of argument values called "evalargs" along with a matrix of basis function values for these argument values called "basismat". You might want too use tags like "args" and "values", respectively for these. You would then assign them to `basisvalues` with code such as the following: basisobj\$basisvalues <- vector("list",1) basisobj\$basisvalues[[1]] <- list(args=evalargs, values=basismat)
`names` | either a character vector of the same length as the number of basis functions or a single character string to which `1:nbasis` are appended as `paste(names, 1:nbasis, sep=''`. For example, if `nbasis = 4`, this defaults to `c('polygon1', 'polygon2', 'polygon3', 'polygon4')`.
`axes` | an optional list used by selected `plot` functions to create custom `axes`. If this `axes` argument is not `NULL`, functions `plot.basisfd`, `plot.fd`, `plot.fdSmooth` `plotfit.fd`, `plotfit.fdSmooth`, and `plot.Lfd` will create axes via `do.call(x$axes[[1]], x$axes[-1])`. The primary example of this uses `list("axesIntervals", ...)`, e.g., with `Fourier` bases to create `CanadianWeather` plots

### Details

The actual basis functions consist of triangles, each with its apex over an argument value. Note that in effect the polygonal basis is identical to a B-spline basis of order 2 and a knot or break value at each argument value. The range of the polygonal basis is set to the interval defined by the smallest and largest argument values.

### Value

a basis object with the type `polyg`.

### See Also

`basisfd`, `create.bspline.basis`, `create.basis`, `create.constant.basis`, `create.exponential.basis`, `create.fourier.basis`, `create.monomial.basis`, `create.power.basis`

### Examples

    #  Create a polygonal basis over the interval [0,1]
    #  with break points at 0, 0.1, ..., 0.95, 1
    (basisobj <- create.polygonal.basis(seq(0,1,0.1)))
    #  plot the basis
    plot(basisobj)

[Package fda version 2.4.8 Index]