Changes for v0.2.1

DESCRIPTION

@@ -2,7 +2,7 @@ Package: FRK
 Type: Package
 Title: Fixed Rank Kriging
 Version: 0.2.1
-Date: 2018-01-12
+Date: 2018-04-12
 Authors@R: c(
     person("Andrew", "Zammit-Mangion", , "andrewzm@gmail.com", c("aut", "cre")))
 Maintainer: Andrew Zammit-Mangion <andrewzm@gmail.com>

NAMESPACE

@@ -44,7 +44,6 @@ export(type)
 exportMethods("$")
 exportMethods("$<-")
 exportMethods("data.frame<-")
-exportMethods(info_fit)
 exportMethods(predict)
 import(Matrix)
 import(dplyr)

R/AllClass.R

@@ -106,6 +106,7 @@ setClass("TensorP_Basis", contains="Basis_obj", representation(Basis1="Basis",Ba
 #' @slot alphahat fixed-effect regression coefficients (estimated)
 #' @slot sigma2fshat fine-scale variation scaling (estimated)
 #' @slot fs_model type of fine-scale variation (independent or CAR-based). Currently only "ind" is permitted
+#' @slot info_fit information on fitting (convergence etc.)
 #' @seealso \code{\link{SRE}} for details on how to construct and fit SRE models.
 #' @keywords spatial
 setClass("SRE",representation(data="list",

R/AllGeneric.R

@@ -208,8 +208,13 @@ setGeneric("BAUs_from_points", function(obj,offset = 1e-10)
 setGeneric("remove_basis", function(Basis,rmidx)
     standardGeneric("remove_basis"))
 
-#' @aliases SRE
+#' @title Retrieve fit information for SRE model
+#' @description Takes a an object of class \code{SRE} and returns a list containing all the relevant information on parameter estimation
+#' @param SRE_model object of class \code{SRE}
 #' @export
+#' @seealso See \code{\link{SRE}} for more information on the SRE model and available fitting methods.
+#' @examples
+#' # See example in the help file for SRE
 setGeneric("info_fit", function(SRE_model)
     standardGeneric("info_fit"))
 

R/SREutils.R

@@ -33,6 +33,7 @@
 #' @param lambda ridge-regression regularisation parameter for when \code{K} is unstructured (0 by default). Can be a single number, or a vector (one parameter for each resolution)
 #' @param print_lik flag indicating whether likelihood value should be printed or not after convergence of the EM estimation algorithm
 # #' @param use_centroid flag indicating whether the basis functions are averaged over the BAU, or whether the basis functions are evaluated at the BAUs centroid in order to construct the matrix \eqn{S}. The flag can safely be set when the basis functions are approximately constant over the BAUs in order to reduce computational time
+#' @param object object of class \code{SRE}
 #' @param newdata object of class \code{SpatialPoylgons} indicating the regions over which prediction will be carried out. The BAUs are used if this option is not specified
 #' @param obs_fs flag indicating whether the fine-scale variation sits in the observation model (systematic error, Case 1) or in the process model (fine-scale process variation, Case 2, default)
 #' @param pred_polys deprecated. Please use \code{newdata} instead
@@ -280,7 +281,7 @@ SRE.fit <- function(SRE_model,n_EM = 100L, tol = 0.01, method="EM", lambda = 0,
 
 }
 
-
+#' @rdname SRE
 #' @export
 SRE.predict <- function(SRE_model, obs_fs = FALSE, newdata = NULL, pred_polys = NULL,
                         pred_time = NULL, covariances = FALSE) {
@@ -370,8 +371,8 @@ summary.SRE <- function(object,...) {
 setMethod("summary",signature(object="SRE"),summary.SRE)
 
 ## Set method for retrieving info_fit
-#' @rdname SRE
-#' @export
+#' @rdname info_fit
+#' @aliases info_fit,SRE-method
 setMethod("info_fit", signature(SRE_model = "SRE"),
           function(SRE_model) {SRE_model@info_fit})
 

demo/00Index

@@ -1,2 +1,2 @@
-FRK-meuse FRK-meuse.R Application of FRK to the meuse dataset. This demo replicates the example given in Section 3.2 of the paper on FRK published in JSS.
-FRK-meuse-BAUs-as-points FRK-meuse-BAUs-as-points.R Application of FRK to the meuse dataset when treating BAUs as points. This demo replicates the example given in Section 3.2 of the paper on FRK published in JSS.
+FRK-meuse	Application of FRK to the meuse dataset. This demo replicates the example given in Section 3.2 of the paper on FRK published in JSS.
+FRK-meuse-BAUs-as-points	Application of FRK to the meuse dataset when treating BAUs as points. This demo replicates the example given in Section 3.2 of the paper on FRK published in JSS.