A 256X256 image of John Lennon.
Try:<p></p><p><code>image(lennon, col=grey.level(256))</code></p>

datasets

lennon

Fields is for curve, surface and function
 fitting with an emphasis on splines, spatial data and spatial
 statistics. The major methods include cubic, robust, and thin plate
 splines, and Kriging for large data sets. The splines and Kriging
 methods are supporting by functions that can determine the smoothing
 parameter (nugget and sill variance) by cross validation and also by
 restricted maximum likelihood.  A major feature is that any
 covariance function implemented in R with the fields interface can be
 used for spatial prediction. Some tailored optimization functions are
 supplied for find the MLEs for the Matern family of covariances.
 There are also many useful functions for plotting and working with
 spatial data as images. This package also contains an implementation
 of a sparse matrix methods for large data sets and currently requires
 the sparse matrix (spam) package for testing (but not for the
 standard spatial functions.) Use help(fields) to get started and for
 an overview.  The fields source code is heavily commented and should
 provide useful explanation of numerical details in addition to the
 manual pages.

lennon: Gray image of John Lennon.

Description

Arguments