X-Git-Url: https://git.auder.net/?p=talweg.git;a=blobdiff_plain;f=pkg%2FR%2FF_Neighbors.R;h=d889a34ce64b82c51889a5a81322a1a7dec25b2c;hp=5b2c8990a850d2dff0d75c23d67815e7393ccd07;hb=ee8b1b4e3c13f8dcf13a2c8da6a3bef1520c8252;hpb=a866acb3c0ae138b22df9dae9ec576b866794417

diff --git a/pkg/R/F_Neighbors.R b/pkg/R/F_Neighbors.R
index 5b2c899..d889a34 100644
--- a/pkg/R/F_Neighbors.R
+++ b/pkg/R/F_Neighbors.R
@@ -31,7 +31,7 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			}
 
 			# Indices of similar days for cross-validation; TODO: 45 = magic number
-			sdays = getSimilarDaysIndices(today, limit=45, same_season=FALSE)
+			sdays = getSimilarDaysIndices(today, data, limit=45, same_season=FALSE)
 
 			cv_days = intersect(fdays,sdays)
 			# Limit to 20 most recent matching days (TODO: 20 == magic number)
@@ -134,7 +134,12 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 					M[i+1,] = c( data$getLevel(fdays[i]), as.double(data$getExo(fdays[i])) )
 
 				sigma = cov(M) #NOTE: robust covariance is way too slow
-				sigma_inv = solve(sigma) #TODO: use pseudo-inverse if needed?
+				# TODO: 10 == magic number; more robust way == det, or always ginv()
+				sigma_inv =
+					if (length(fdays) > 10)
+						solve(sigma)
+					else
+						MASS::ginv(sigma)
 
 				# Distances from last observed day to days in the past
 				distances2 = sapply(seq_along(fdays), function(i) {
@@ -143,7 +148,7 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 				})
 
 				sd_dist = sd(distances2)
-				if (sd_dist < .Machine$double.eps)
+				if (sd_dist < .25 * sqrt(.Machine$double.eps))
 				{
 #					warning("All computed distances are very close: stdev too small")
 					sd_dist = 1 #mostly for tests... FIXME: