2014-12-02: 100 ensemble members with 30 noise.

100 ensemble members with 30 noise.

diff --git a/examples/ensemble-estimation.w b/examples/ensemble-estimation.w
--- a/examples/ensemble-estimation.w
+++ b/examples/ensemble-estimation.w
@@ -112,7 +112,7 @@ x are parameters to be optimized, pos is
 ;; the equivalent of measured observations
 define y^true : list-ec (: i y⁰-pos) : H x^true i
 ;; now we disturb the observations with a fixed standard deviation. This assumes uncorrelated observations.
-define y⁰-std 100
+define y⁰-std 30
 define y⁰ : list-ec (: i y^true) : + i : * y⁰-std : random:normal
 ;; and define the covariance matrix. This assumes uncorrelated observations.
 define R : make-covariance-matrix-from-standard-deviations : list-ec (: i y⁰-num) y⁰-std
@@ -197,7 +197,7 @@ Limitations: y is a single value. R and 
 
 define : main args
     let*
-      : optimized : EnSRT H x^b P y⁰ R y⁰-pos 30
+      : optimized : EnSRT H x^b P y⁰ R y⁰-pos 100
         x-opt : list-ref optimized 0
         x-deviations : list-ref optimized 1
         ; std : sqrt : * {1 / {(length x-deviations) - 1}} : sum-ec (: i x-deviations) : expt i 2