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spatstat (version 1.33-0)

as.fv: Convert Data To Class fv

Description

Converts data into a function table (an object of class "fv").

Usage

as.fv(x)

## S3 method for class 'fv': as.fv(x)

## S3 method for class 'data.frame': as.fv(x)

## S3 method for class 'matrix': as.fv(x)

## S3 method for class 'fasp': as.fv(x)

## S3 method for class 'minconfit': as.fv(x)

## S3 method for class 'kppm': as.fv(x)

## S3 method for class 'bw.optim': as.fv(x)

Arguments

x
Data which will be converted into a function table

Value

Details

This command converts data x, that could be interpreted as the values of a function, into a function value table (object of the class "fv" as described in fv.object). This object can then be plotted easily using plot.fv.

The dataset x may be any of the following:

  • an object of class"fv";
  • a matrix or data frame with at least two columns;
  • an object of class"fasp", representing an array of"fv"objects.
  • an object of class"minconfit", giving the results of a minimum contrast fit by the commandmincontrast. The
  • an object of class"kppm", representing a fitted Cox or cluster point process model, obtained from the model-fitting commandkppm;
  • an object of class"bw.optim", representing an optimal choice of smoothing bandwidth by a cross-validation method, obtained from commands likebw.diggle.
The function as.fv is generic, with methods for each of the classes listed above. The behaviour is as follows:
  • Ifxis an object of class"fv", it is returned unchanged.
  • Ifxis a matrix or data frame, the first column is interpreted as the function argument, and subsequent columns are interpreted as values of the function computed by different methods.
  • Ifxis an object of class"fasp"representing an array of"fv"objects, these are combined into a single"fv"object.
  • Ifxis an object of class"minconfit", or an object of class"kppm"that was fitted by minimum contrast, the result is a function table containing the observed summary function and the best fit summary function.
  • Ifxis an object of class"bw.optim", the result is a function table of the optimisation criterion as a function of the smoothing bandwidth.

Examples

Run this code
r <- seq(0, 1, length=101)
  x <- data.frame(r=r, y=r^2)
  as.fv(x)

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