Package: latticeDensity
Type: Package
Title: Density estimation and nonparametric regression on irregular
regions
Version: 1.0.7
Date: 2012-01-06
Author: Ronald Barry <rpbarry@alaska.edu>
Maintainer: Ronald Barry <rpbarry@alaska.edu>
Depends: splancs, spdep, spatstat, spam
Description: This package contains functions that compute the
lattice-based density estimator of Barry and McIntyre, which
accounts for point processes in two-dimensional regions with
irregular boundaries and holes. The package also implements
two-dimensional non-parametric regression for similar regions.
License: GPL-2
URL: www.r-project.org
Packaged: 2012-01-07 01:17:55 UTC; Ronald Barry
Repository: CRAN
Date/Publication: 2012-01-07 05:44:22
Package: GPFDA
Title: Apply Gaussian Process in Functional data analysis
Version: 2.2
Date: 2014-09-26
Depends: R (>= 3.1), fda.usc, spam, fda
Imports: MASS
Author: Jian Qing Shi, Yafeng Cheng
Maintainer: Yafeng Cheng <yafeng.cheng@ncl.ac.uk>
Description: Use functional regression as the mean structure and Gaussian Process as the covariance structure.
License: GPL-3
Packaged: 2014-09-29 19:29:28 UTC; a9590288
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-09-29 23:38:33
Package: LatticeKrig
Version: 5.5
Date: 2016-05-21
Title: Multiresolution Kriging Based on Markov Random Fields
Author: Douglas Nychka [aut, cre], Dorit Hammerling [aut], Stephan Sain [aut], Nathan Lenssen [aut]
Authors@R: c(
person("Douglas", "Nychka", role = c("aut", "cre"),
email = "nychka@ucar.edu"),
person("Dorit", "Hammerling", role = c("aut"),
email = "hammerling@samsi.info"),
person("Stephan", "Sain", role = "aut",
email = "ssain@ucar.edu"),
person("Nathan", "Lenssen", role = "aut",
email = "lenssen@ucar.edu"))
Maintainer: Douglas Nychka <nychka@ucar.edu>
Description: Methods for the interpolation of large spatial
datasets. This package follows a "fixed rank Kriging" approach using
a large number of basis functions and provides spatial estimates
that are comparable to standard families of covariance functions.
Using a large number of basis functions allows for estimates that
can come close to interpolating the observations (a spatial model
with a small nugget variance.) Moreover, the covariance model for
this method can approximate the Matern covariance family but also
allows for a multi-resolution model and supports efficient
computation of the profile likelihood for estimating covariance
parameters. This is accomplished through compactly supported basis
functions and a Markov random field model for the basis
coefficients. These features lead to sparse matrices for the
computations and this package makes of the R spam package for this.
An extension of this version over previous ones ( < 5.4 ) is the
support for different geometries besides a rectangular domain. The
Markov random field approach combined with a basis function
representation makes the implementation of different geometries
simple where only a few specific functions need to be added with
most of the computation and evaluation done by generic routines that
have been tuned to be efficient. One benefit of the LatticeKrig
model/approach is the facility to do unconditional and conditional
simulation of the field for large numbers of arbitrary points. There
is also the flexibility for estimating non-stationary covariances
and also the case when the observations are a linear combination
(e.g. an integral) of the spatial process. Included are generic
methods for prediction, standard errors for prediction, plotting of
the estimated surface and conditional and unconditional simulation.
License: GPL (>= 2)
URL: http://www.r-project.org
Depends: R (>= 3.0.1), methods, spam, fields (>= 6.9.1)
Packaged: 2016-05-21 14:22:35 UTC; nychka
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2016-05-22 09:20:48
Package: excursions
Type: Package
Title: Excursion Sets and Contour Credibility Regions for Random Fields
Version: 2.1.1
Date: 2016-03-10
Author: David Bolin <davidbolin@gmail.com> and Finn Lindgren <finn.lindgren@gmail.com>
Maintainer: David Bolin <davidbolin@gmail.com>
Description: Functions that compute probabilistic excursion sets, contour credibility regions, contour avoiding regions, and simultaneous confidence bands for latent gaussian random processes and fields. The package also contains functions that calculate these quantities for models estimated with the INLA package.
Depends: Matrix, sp, spam
Imports: methods, stats, graphics
Suggests: INLA, testthat, rgeos
Additional_repositories: https://www.math.ntnu.no/inla/R/stable
License: GPL (>= 3)
Copyright: The R package and code, and the main programs, were written
by and are Copyright by David Bolin and Finn Lindgren, and are
redistributable under the GNU Public License, version 3 or
later. The package also includes code from the libraries CAMD
from the SuiteSparse collection of Tim Davis, as well as
functions from the GNU Scientific library and the RngStreams
library by Pierre L'Ecuyer. For details see the COPYRIGHTS
file.
NeedsCompilation: yes
Packaged: 2016-03-10 19:24:56 UTC; davidbolin
Repository: CRAN
Date/Publication: 2016-03-10 23:38:01
Package: fields
Version: 8.4-1
Date: 2016-05-05
Title: Tools for Spatial Data
Authors@R: c( person("Douglas", "Nychka", role = c("aut", "cre"),
email = "nychka@ucar.edu"),
person("Reinhard", "Furrer", role = c("aut"),
email = "reinhard.furrer@math.uzh.ch"),
person("John", "Paige", role = c("aut"),
email = "paigejo@uw.edu"),
person("Stephan", "Sain", role = "aut",
email = "ssain@ucar.edu"))
Author: Douglas Nychka [aut, cre], Reinhard Furrer [aut], John Paige [aut], Stephan Sain [aut]
Maintainer: Douglas Nychka <nychka@ucar.edu>
Description: For curve, surface and function fitting with an emphasis
on splines, spatial data and spatial statistics. The major methods
include cubic, and thin plate splines, Kriging and compact
covariances for large data sets. The splines and Kriging methods are
supported by functions that can determine the smoothing parameter
(nugget and sill variance) and other covariance parameters by cross
validation and also by restricted maximum likelihood. For Kriging
there is an easy to use function that also estimates the correlation
scale (range). A major feature is that any covariance function
implemented in R and following a simple fields format can be used for
spatial prediction. There are also many useful functions for plotting
and working with spatial data as images. This package also contains
an implementation of sparse matrix methods for large spatial data
sets and currently requires the sparse matrix (spam) package. Use
help(fields) to get started and for an overview. The fields source
code is deliberately commented and provides useful explanations of
numerical details in addition to the manual pages. The commented
source code can be viewed by expanding the source code file (ending in tar.gz)
and looking in the R subdirectory. Please cite fields along with its
DOI in your publications!
License: GPL (>= 2)
URL: http://www.image.ucar.edu/fields
Depends: R (>= 3.0), methods, spam, maps
NeedsCompilation: yes
Packaged: 2016-05-05 16:13:09 UTC; nychka
Repository: CRAN
Date/Publication: 2016-05-05 23:56:26
Package: spThin
Type: Package
Title: Functions for Spatial Thinning of Species Occurrence Records for
Use in Ecological Models
Version: 0.1.0
Date: 2014-11-16
Author: Matthew E. Aiello-Lammens, Robert A. Boria, Aleksandar Radosavljevic,
Bruno Vilela, and Robert P. Anderson
Maintainer: Matthew E. Aiello-Lammens <matt.lammens@gmail.com>
Description: spThin is a set of functions that can be used to spatially thin
species occurrence data. The resulting thinned data can be used in ecological
modeling, such as ecological niche modeling.
Depends: spam, grid, fields, knitr
LazyData: TRUE
License: GPL-3
VignetteBuilder: knitr
Packaged: 2014-11-17 02:17:13 UTC; mlammens
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-11-17 08:57:55
providing 
.