{"action":"created","comment":{"url":"https://api.github.com/repos/geotrellis/geotrellis/pulls/comments/36886718","id":36886718,"diff_hunk":"@@ -0,0 +1,187 @@\n+/*\n+* Copyright (c) 2015 Azavea.\n+*\n+* Licensed under the Apache License, Version 2.0 (the \"License\");\n+* you may not use this file except in compliance with the License.\n+* You may obtain a copy of the License at\n+*\n+* http://www.apache.org/licenses/LICENSE-2.0\n+*\n+* Unless required by applicable law or agreed to in writing, software\n+* distributed under the License is distributed on an \"AS IS\" BASIS,\n+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n+* See the License for the specific language governing permissions and\n+* limitations under the License.\n+*/\n+\n+package geotrellis.raster.interpolation\n+\n+import geotrellis.vector.PointFeature\n+import geotrellis.vector.Point\n+import geotrellis.vector.interpolation.{NonLinearSemivariogram, ModelType, Semivariogram}\n+\n+import org.apache.commons.math3.linear._\n+\n+import spire.syntax.cfor._\n+\n+/**\n+ * @param points          Sample points for Universal Kriging model training\n+ * @param attrFunc        Attribute matrix transformation for a point (which decides how the point coordinates guide the pointData's value)\n+ * @param bandwidth       The maximum inter-point pair-distances which influence the prediction\n+ * @param model           The [[ModelType]] to be used for prediction\n+ */\n+class UniversalKriging(points: Array[PointFeature[Double]],\n+                       attrFunc: (Double, Double) => Array[Double],\n+                       bandwidth: Double,\n+                       model: ModelType) extends Kriging {\n+  /**\n+   * Overloaded constructor, for default attribute matrix generation\n+   */\n+  def this(points: Array[PointFeature[Double]], bandwidth: Double, model: ModelType) 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companion object `apply`","created_at":"2015-08-12T17:15:27Z","updated_at":"2015-08-12T17:15:27Z","html_url":"https://github.com/geotrellis/geotrellis/pull/1103#discussion_r36886718","pull_request_url":"https://api.github.com/repos/geotrellis/geotrellis/pulls/1103","_links":{"self":{"href":"https://api.github.com/repos/geotrellis/geotrellis/pulls/comments/36886718"},"html":{"href":"https://github.com/geotrellis/geotrellis/pull/1103#discussion_r36886718"},"pull_request":{"href":"https://api.github.com/repos/geotrellis/geotrellis/pulls/1103"}}},"pull_request":{"url":"https://api.github.com/repos/geotrellis/geotrellis/pulls/1103","id":36561501,"html_url":"https://github.com/geotrellis/geotrellis/pull/1103","diff_url":"https://github.com/geotrellis/geotrellis/pull/1103.diff","patch_url":"https://github.com/geotrellis/geotrellis/pull/1103.patch","issue_url":"https://api.github.com/repos/geotrellis/geotrellis/issues/1103","number":1103,"state":"open","locked":false,"title":"WIP: Kriging 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Ordinary, Universal and Geostatistical methods of Kriging; along with Spherical, Gaussian, Exponential, Circular, Wave and Linear semivariogram 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