tag:crantastic.org,2005:/packages/fieldsLatest activity for fields2020-02-04T16:41:29Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/982792020-02-04T16:41:29Z2020-02-04T16:41:29Zfields was upgraded to version 10.3<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/93376">10.3</a><br /><h3>Package description:</h3><p>For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/981412020-02-02T17:41:30Z2020-02-02T17:41:30Zfields was upgraded to version 10.2<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/93247">10.2</a><br /><h3>Package description:</h3><p>For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/946452019-11-11T23:01:39Z2019-11-11T23:01:39Zfields was upgraded to version 10.0<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/89990">10.0</a><br /><h3>Package description:</h3><p>For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/936812019-10-13T17:41:13Z2019-10-13T17:41:13Zfields was upgraded to version 9.9<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/89049">9.9</a><br /><h3>Package description:</h3><p>For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/916742019-08-19T18:01:29Z2019-08-19T18:01:29Zfields was upgraded to version 9.8-6<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/87163">9.8-6</a><br /><h3>Package description:</h3><p>For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/889862019-05-28T21:41:21Z2019-05-28T21:41:21Zfields was upgraded to version 9.8-3<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/84604">9.8-3</a><br /><h3>Package description:</h3><p>For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/884172019-05-14T21:21:15Z2019-05-14T21:21:15Zfields was upgraded to version 9.8-1<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/84051">9.8-1</a><br /><h3>Package description:</h3><p>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 compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/875442019-04-23T13:01:20Z2019-04-23T13:01:20Zfields was upgraded to version 9.7<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/83229">9.7</a><br /><h3>Package description:</h3><p>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 compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research. See the Fields URL for a vignette on using this package and some background on spatial statistics.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/874862019-04-22T07:21:28Z2019-04-22T07:21:28Zfields was upgraded to version 9.6.1<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/83171">9.6.1</a><br /><h3>Package description:</h3><p>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 compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/710102018-01-29T23:21:11Z2018-01-29T23:21:11Zfields was upgraded to version 9.6<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/67812">9.6</a><br /><h3>Package description:</h3><p>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 compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/632612017-06-06T17:21:11Z2017-06-06T17:21:11Zfields was upgraded to version 9.0<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/60500">9.0</a><br /><h3>Package description:</h3><p>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 compactly supported covariance functions 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 function 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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/624742017-05-11T18:40:48Z2017-05-11T18:40:48Zfields was upgraded to version 8.15<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/59731">8.15</a><br /><h3>Package description:</h3><p>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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 as a companion to the manual pages. The commented source code can be viewed by expanding the package source code "tarball" (ending in tar.gz) and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/577862016-12-16T22:41:10Z2016-12-16T22:41:10Zfields was upgraded to version 8.10<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/55331">8.10</a><br /><h3>Package description:</h3><p>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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 package source code "tarball" (ending in tar.gz) and looking in the R subdirectory. Please cite fields along with its DOI in your publications!</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/577562016-12-16T10:20:45Z2016-12-16T10:20:45Zfields was upgraded to version 8.8<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/55301">8.8</a><br /><h3>Package description:</h3><p>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 parameter). A major feature is that any covariance function implemented in R and following a simple 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 package source code "tarball" (ending in tar.gz) and looking in the R subdirectory. Please cite fields along with its DOI in your publications!</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/576212016-12-13T07:20:50Z2016-12-13T07:20:50Zfields was upgraded to version 8.7<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/55172">8.7</a><br /><h3>Package description:</h3><p>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!</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/512442016-05-16T04:05:48Z2016-05-16T04:05:48Zhaminhyoung uses fields<a href="/users/1926">haminhyoung</a> <span class="action">uses</span> <a href="/packages/fields">fields</a>haminhyoungtag:crantastic.org,2005:TimelineEvent/509612016-05-05T22:00:54Z2016-05-05T22:00:54Zfields was upgraded to version 8.4-1<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/49244">8.4-1</a><br /><h3>Package description:</h3><p>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!</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/462352016-01-04T10:11:03Z2016-01-04T10:11:03Zfields was upgraded to version 8.3-6<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/46006">8.3-6</a><br /><h3>Package description:</h3><p>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 supporting by functions that can determine the smoothing parameter (nugget and sill variance) by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to 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 .tar.gz file and looking in R subdirectory.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/444312015-10-15T23:31:10Z2015-10-15T23:31:10Zfields was upgraded to version 8.3-5<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/44223">8.3-5</a><br /><h3>Package description:</h3><p>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 supporting by functions that can determine the smoothing parameter (nugget and sill variance) by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to 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 .tar.gz file and looking in R subdirectory.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/392942015-02-28T06:10:50Z2015-02-28T06:10:50Zfields was upgraded to version 8.2-1<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/39119">8.2-1</a><br /><h3>Package description:</h3><p>Fields is 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 supporting by functions that can determine the smoothing parameter (nugget and sill variance) by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to 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 .tar.gz file and looking in R subdirectory.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/343702013-07-19T21:50:27Z2013-07-19T21:50:27Zfields was upgraded to version 6.8<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/29420">6.8</a><br /><h3>Package description:</h3><p>Fields is 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 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 (simple) fields format can be used for spatial prediction. Some tailored optimization functions are supplied for finding 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 sparse matrix methods for large data sets and currently requires the sparse matrix (spam) package for testing and use with large data sets. But spam is not required for the standard spatial functions. Use help(fields) to get started and for an overview. The fields source code is heavily commented and provides useful explanations of numerical details in addition to the manual pages.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/320052013-04-21T06:10:25Z2013-04-21T06:10:25Zfields was upgraded to version 6.7.6<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/27209">6.7.6</a><br /><h3>Package description:</h3><p>Fields is 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 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 (simple) fields format can be used for spatial prediction. Some tailored optimization functions are supplied for finding 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 sparse matrix methods for large data sets and currently requires the sparse matrix (spam) package for testing and use with large data sets. But spam is not required for the standard spatial functions. Use help(fields) to get started and for an overview. The fields source code is heavily commented and provides useful explanations of numerical details in addition to the manual pages.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/319402013-04-18T21:10:24Z2013-04-18T21:10:24Zfields was upgraded to version 6.7.5<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/27155">6.7.5</a><br /><h3>Package description:</h3><p>Fields is 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 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 (simple) fields format can be used for spatial prediction. Some tailored optimization functions are supplied for finding 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 sparse matrix methods for large data sets and currently requires the sparse matrix (spam) package for testing and use with large data sets. But spam is not required for the standard spatial functions. Use help(fields) to get started and for an overview. The fields source code is heavily commented and provides useful explanations of numerical details in addition to the manual pages.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/261822012-10-16T19:11:00Z2012-10-16T19:11:00Zfields was upgraded to version 6.7<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/22109">6.7</a><br /><h3>Package description:</h3><p>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.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/186592012-01-10T23:12:22Z2012-01-10T23:12:22Zfields was upgraded to version 6.6.3<a href="/packages/fields">fields</a> was <span class="action">upgraded</span> to version <a href="/packages/fields/versions/16348">6.6.3</a><br /><h3>Package description:</h3><p>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.</p>crantastic.org