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Task/Multiple-regression/ERRE/multiple-regression.erre

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+PROGRAM MULTIPLE_REGRESSION
+
+!$DOUBLE
+
+CONST N=14,M=2,Q=3 ! number of points and M.R. polynom degree
+
+DIM X[N],Y[N]      ! data points
+DIM S[N],T[N]      ! linear system coefficient
+DIM A[M,Q]         ! sistem to be solved
+
+BEGIN
+
+   DATA(1.47,1.50,1.52,1.55,1.57,1.60,1.63,1.65,1.68,1.70,1.73,1.75,1.78,1.80,1.83)
+   DATA(52.21,53.12,54.48,55.84,57.20,58.57,59.93,61.29,63.11,64.47,66.28,68.10,69.92,72.19,74.46)
+
+   FOR I%=0 TO N DO
+     READ(X[I%])
+   END FOR
+
+   FOR I%=0 TO N DO
+     READ(Y[I%])
+   END FOR
+
+   FOR K%=0 TO 2*M DO
+      S[K%]=0  T[K%]=0
+      FOR I%=0 TO N DO
+         S[K%]=S[K%]+X[I%]^K%
+         IF K%<=M THEN T[K%]=T[K%]+Y[I%]*X[I%]^K% END IF
+      END FOR
+   END FOR
+
+! build linear system
+
+   FOR ROW%=0 TO M DO
+     FOR COL%=0 TO M DO
+       A[ROW%,COL%]=S[ROW%+COL%]
+     END FOR
+     A[ROW%,COL%]=T[ROW%]
+   END FOR
+
+   PRINT("LINEAR SYSTEM COEFFICENTS") PRINT
+   FOR I%=0 TO M DO
+     FOR J%=0 TO M+1 DO
+        WRITE(" ######.#";A[I%,J%];)
+     END FOR
+     PRINT
+   END FOR
+   PRINT
+
+   FOR J%=0 TO M DO
+         FOR I%=J% TO M DO
+              EXIT IF A[I%,J%]<>0
+         END FOR
+         IF I%=M+1 THEN
+             PRINT("SINGULAR MATRIX !")
+             !$STOP
+         END IF
+         FOR K%=0 TO M+1 DO
+             SWAP(A[J%,K%],A[I%,K%])
+         END FOR
+         Y=1/A[J%,J%]
+         FOR K%=0 TO M+1 DO
+             A[J%,K%]=Y*A[J%,K%]
+         END FOR
+         FOR I%=0 TO M DO
+             IF I%<>J% THEN
+                 Y=-A[I%,J%]
+                 FOR K%=0 TO M+1 DO
+                    A[I%,K%]=A[I%,K%]+Y*A[J%,K%]
+                 END FOR
+             END IF
+         END FOR
+   END FOR
+   PRINT
+
+   PRINT("SOLUTIONS") PRINT
+   FOR I%=0 TO M DO
+      PRINT("c";I%;"=";)
+      WRITE("#####.#######";A[I%,M+1])
+   END FOR
+
+END PROGRAM

Task/Multiple-regression/Hy/multiple-regression.hy

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+(import
+  [numpy [ones column-stack]]
+  [numpy.random [randn]]
+  [numpy.linalg [lstsq]])
+
+(setv n 1000)
+(setv x1 (randn n))
+(setv x2 (randn n))
+(setv y (+ 3 (* 1 x1) (* -2 x2) (* .25 x1 x2) (randn n)))
+
+(print (first (lstsq
+  (column-stack (, (ones n) x1 x2 (* x1 x2)))
+  y)))