dane = [64.20   63.00   62.50   63.10
65.40   64.20   63.00   62.50
69.50   65.40   64.20   63.00
72.80   69.50   65.40   64.20
74.85   72.80   69.50   65.40
74.00   74.85   72.80   69.50
74.50   74.00   74.85   72.80
75.50   74.50   74.00   74.85
75.40   75.50   74.50   74.00
73.65   75.40   75.50   74.50
71.70   73.65   75.40   75.50
72.25   71.70   73.65   75.40
73.10   72.25   71.70   73.65
73.50   73.10   72.25   71.70
72.75   73.50   73.10   72.25
72.40   72.75   73.50   73.10
72.95   72.40   72.75   73.50
73.00   72.95   72.40   72.75
72.80   73.00   72.95   72.40
72.70   72.80   73.00   72.95
73.50   72.70   72.80   73.00
73.00   73.50   72.70   72.80
70.80   73.00   73.50   72.70
70.00   70.80   73.00   73.50
71.15   70.00   70.80   73.00
70.00   71.15   70.00   70.80
70.00   70.00   71.15   70.00
71.00   70.00   70.00   71.15
70.50   71.00   70.00   70.00
70.00   70.50   71.00   70.00
70.70   70.00   70.50   71.00
70.00   70.70   70.00   70.50
70.20   70.00   70.70   70.00
71.00   70.20   70.00   70.70
70.85   71.00   70.20   70.00
68.00   70.85   71.00   70.20
69.95   68.00   70.85   71.00
69.80   69.95   68.00   70.85
69.30   69.80   69.95   68.00
68.95   69.30   69.80   69.95
69.65   68.95   69.30   69.80
70.20   69.65   68.95   69.30
69.90   70.20   69.65   68.95
66.85   69.90   70.20   69.65
68.40   66.85   69.90   70.20
67.90   68.40   66.85   69.90
67.00   67.90   68.40   66.85
66.60   67.00   67.90   68.40
66.50   66.60   67.00   67.90
69.00   66.50   66.60   67.00
69.50   69.00   66.50   66.60
68.75   69.50   69.00   66.50
69.40   68.75   69.50   69.00
69.00   69.40   68.75   69.50
69.75   69.00   69.40   68.75
69.50   69.75   69.00   69.40
68.50   69.50   69.75   69.00
68.00   68.50   69.50   69.75
68.50   68.00   68.50   69.50
68.25   68.50   68.00   68.50
68.01   68.25   68.50   68.00
68.00   68.01   68.25   68.50
66.70   68.00   68.01   68.25
67.00   66.70   68.00   68.01
67.00   67.00   66.70   68.00
66.75   67.00   67.00   66.70
67.10   66.75   67.00   67.00
67.00   67.10   66.75   67.00
67.80   67.00   67.10   66.75
69.35   67.80   67.00   67.10
71.00   69.35   67.80   67.00
69.60   71.00   69.35   67.80
69.69   69.60   71.00   69.35
69.45   69.69   69.60   71.00
69.49   69.45   69.69   69.60
72.50   69.49   69.45   69.69
73.95   72.50   69.49   69.45
73.20   73.95   72.50   69.49
73.65   73.20   73.95   72.50
75.00   73.65   73.20   73.95
80.00   75.00   73.65   73.20
79.40   80.00   75.00   73.65
80.30   79.40   80.00   75.00
81.00   80.30   79.40   80.00
84.00   81.00   80.30   79.40
83.80   84.00   81.00   80.30
83.00   83.80   84.00   81.00
82.50   83.00   83.80   84.00
84.00   82.50   83.00   83.80
83.99   84.00   82.50   83.00
83.80   83.99   84.00   82.50
83.38   83.80   83.99   84.00
86.00   83.38   83.80   83.99
88.50   86.00   83.38   83.80
88.44   88.50   86.00   83.38
88.00   88.44   88.50   86.00
91.00   88.00   88.44   88.50
90.50   91.00   88.00   88.44
89.70   90.50   91.00   88.00
86.65   89.70   90.50   91.00
89.88   86.65   89.70   90.50
90.29   89.88   86.65   89.70
93.90   90.29   89.88   86.65
94.00   93.90   90.29   89.88
90.70   94.00   93.90   90.29
90.00   90.70   94.00   93.90
88.70   90.00   90.70   94.00
87.21   88.70   90.00   90.70
86.30   87.21   88.70   90.00
84.99   86.30   87.21   88.70
89.50   84.99   86.30   87.21
90.00   89.50   84.99   86.30
89.50   90.00   89.50   84.99
87.50   89.50   90.00   89.50
86.50   87.50   89.50   90.00
84.00   86.50   87.50   89.50
85.45   84.00   86.50   87.50
86.90   85.45   84.00   86.50
87.00   86.90   85.45   84.00
87.00   87.00   86.90   85.45
88.65   87.00   87.00   86.90
88.00   88.65   87.00   87.00
86.50   88.00   88.65   87.00
88.00   86.50   88.00   88.65
87.11   88.00   86.50   88.00
88.20   87.11   88.00   86.50
86.00   88.20   87.11   88.00
87.50   86.00   88.20   87.11
87.45   87.50   86.00   88.20
86.97   87.45   87.50   86.00
86.22   86.97   87.45   87.50
84.55   86.22   86.97   87.45
85.50   84.55   86.22   86.97
85.02   85.50   84.55   86.22
86.75   85.02   85.50   84.55
87.50   86.75   85.02   85.50
]


yk = dane(:,1)
//to co chcemy przewidzieć, nie ma kolumny x

F = dane(:,2:4)
//dane na podstawie których chcemy przewidzieć przyszłość (yk)

V = pinv(F)*yk
//obliczanie macierzy współczynników

plot (yk)
//wykres danych

plot (V(1)*F(:,1) + V(2)*F(:,2) + V(3)*F(:,3), 'g-')
//wykres odpowiedzi modelu

Predict = V(1)*F(:,1) + V(2)*F(:,2) + V(3)*F(:,3)
//obliczenie odpowiedzi modelu (to samo co wyżej wrzucono na wykres)

err = Predict - yk
//jednowymiarowa macierz błędów

print(err'*err)