[Analogue-commits] r206 - in pkg: R inst

[noreply at r-forge.r-project.org]

Author: gsimpson
Date: 2011-01-29 00:24:42 +0100 (Sat, 29 Jan 2011)
New Revision: 206

Modified:
   pkg/R/fixUpTol.R
   pkg/R/predict.wa.R
   pkg/inst/ChangeLog
Log:
fix bugs in bootstrap and k-fold CV, plus silly stop criterion in fixUpTol

Modified: pkg/R/fixUpTol.R
===================================================================
--- pkg/R/fixUpTol.R	2011-01-28 23:18:11 UTC (rev 205)
+++ pkg/R/fixUpTol.R	2011-01-28 23:24:42 UTC (rev 206)
@@ -10,9 +10,12 @@
     }
     ## second, replace tol < min.tol
     if(!is.null(min.tol) && any(MIN.TOL <- tol < min.tol)) {
-        ## min.tol must be in or on extremesof range(env)
-        if(min.tol < min(env) || min.tol > max(env))
-            stop("'min.tol' must be >= min(env) and <= max(env)")
+        ## min.tol must be in or on extremes of range(tol)
+        ## originally had min(env) and max(env), but that doesn't make sense
+        ## I think the point was to stop user supplying too low tolerances
+        ## but this has nothing to do with the range of the environment
+        if(min.tol < min(tol) || min.tol > max(tol))
+            stop("'min.tol' must be >= min(tol) and <= max(tol)")
         if(small.tol == "fraction")
             frac <- f * diff(range(env))
         tol[MIN.TOL] <-

Modified: pkg/R/predict.wa.R
===================================================================
--- pkg/R/predict.wa.R	2011-01-28 23:18:11 UTC (rev 205)
+++ pkg/R/predict.wa.R	2011-01-28 23:24:42 UTC (rev 206)
@@ -104,11 +104,11 @@
                 wa.optima <- w.avg(X[sel,,drop = FALSE], ENV[sel])
                 ## CV for the training set
                 if(object$tol.dw) {
-                    tol <- w.tol(X[sel, , drop = FALSE], ENV[-sel],
+                    tol <- w.tol(X[sel, , drop = FALSE], ENV[sel],
                                  wa.optima, useN2 = useN2)
                     ## fix up problematic tolerances
                     tol <- fixUpTol(tol, O$na.tol, O$small.tol,
-                                    O$min.tol, O$f, ENV[-sel])
+                                    O$min.tol, O$f, ENV[sel])
                     wa.env <- WATpred(X[sel, , drop = FALSE],
                                       wa.optima, tol, nr, nc)
                     pred <- WATpred(X[-sel, ,drop=FALSE], wa.optima,
@@ -155,11 +155,11 @@
                     wa.optima <- w.avg(X[sel,], ENV[sel])
                     ## CV for the training set
                     if(object$tol.dw) {
-                        tol <- w.tol(X[sel, , drop = FALSE], ENV[-sel],
+                        tol <- w.tol(X[sel, , drop = FALSE], ENV[sel],
                                      wa.optima, useN2 = useN2)
                         ## fix up problematic tolerances
                         tol <- fixUpTol(tol, O$na.tol, O$small.tol,
-                                        O$min.tol, O$f, ENV[-sel])
+                                        O$min.tol, O$f, ENV[sel])
                         wa.env <- WATpred(X[sel, , drop = FALSE],
                                           wa.optima, tol, nr, nc)
                         pred <- WATpred(X[-sel, ,drop=FALSE], wa.optima,

Modified: pkg/inst/ChangeLog
===================================================================
--- pkg/inst/ChangeLog	2011-01-28 23:18:11 UTC (rev 205)
+++ pkg/inst/ChangeLog	2011-01-28 23:24:42 UTC (rev 206)
@@ -49,6 +49,12 @@
 	the package tarball size considerably. As a result, however,
 	analogue now requires R version 2.10.0 or later.
 
+	* predict.wa: bug in bootstrap and k-fold CV methods when
+	tolerance down-weighting was used.
+
+	* fixUpTol: erroneous error criterion would cause CV of WA models
+	with tolerance down-weighting to stop with an error.
+
 Version 0.6-26
 
 	* abernethy: New data set containing the classic Abernethy Forest