Data update

Task/Polynomial-regression/EasyLang/polynomial-regression.easy

@@ -0,0 +1,40 @@
+func eval a b c x .
+   return a + (b + c * x) * x
+.
+proc regression xa[] ya[] . .
+   n = len xa[]
+   for i = 1 to n
+      xm = xm + xa[i]
+      ym = ym + ya[i]
+      x2m = x2m + xa[i] * xa[i]
+      x3m = x3m + xa[i] * xa[i] * xa[i]
+      x4m = x4m + xa[i] * xa[i] * xa[i] * xa[i]
+      xym = xym + xa[i] * ya[i]
+      x2ym = x2ym + xa[i] * xa[i] * ya[i]
+   .
+   xm = xm / n
+   ym = ym / n
+   x2m = x2m / n
+   x3m = x3m / n
+   x4m = x4m / n
+   xym = xym / n
+   x2ym = x2ym / n
+   #
+   sxx = x2m - xm * xm
+   sxy = xym - xm * ym
+   sxx2 = x3m - xm * x2m
+   sx2x2 = x4m - x2m * x2m
+   sx2y = x2ym - x2m * ym
+   #
+   b = (sxy * sx2x2 - sx2y * sxx2) / (sxx * sx2x2 - sxx2 * sxx2)
+   c = (sx2y * sxx - sxy * sxx2) / (sxx * sx2x2 - sxx2 * sxx2)
+   a = ym - b * xm - c * x2m
+   print "y = " & a & " + " & b & "x + " & c & "x^2"
+   numfmt 0 3
+   for i = 1 to n
+      print xa[i] & "  " & ya[i] & " " & eval a b c xa[i]
+   .
+.
+xa[] = [ 0 1 2 3 4 5 6 7 8 9 10 ]
+ya[] = [ 1 6 17 34 57 86 121 162 209 262 321 ]
+regression xa[] ya[]

Task/Polynomial-regression/Raku/polynomial-regression.raku

@@ -1,4 +1,4 @@
-use Clifford;
+use MultiVector;
 
 constant @x1 = <0 1 2 3 4 5 6 7 8 9 10>;
 constant @y = <1 6 17 34 57 86 121 162 209 262 321>;
@@ -9,12 +9,7 @@ constant $x2 = [+] @x1 »**» 2  Z* @e;
 
 constant $y  = [+] @y Z* @e;
 
-my $J = $x1 ∧ $x2;
-my $I = $x0 ∧ $J;
-
-my $I2 = ($I·$I.reversion).Real;
-
 .say for
-(($y ∧ $J)·$I.reversion)/$I2,
-(($y ∧ ($x2 ∧ $x0))·$I.reversion)/$I2,
-(($y ∧ ($x0 ∧ $x1))·$I.reversion)/$I2;
+  $y∧$x1∧$x2/($x0∧$x1∧$x2),
+  $y∧$x2∧$x0/($x1∧$x2∧$x0),
+  $y∧$x0∧$x1/($x2∧$x0∧$x1);