Теория массового обслуживания. Сивохин А.В - 44 стр.

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44
W3:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[3,i],i=1..m)], z, form=Lagrange ):
W4:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[4,i],i=1..m)], z, form=Lagrange ):
W5:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[5,i],i=1..m)], z, form=Lagrange ):
W6:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[6,i],i=1..m)], z, form=Lagrange ):
W7:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[7,i],i=1..m)], z, form=Lagrange ):
W8:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[8,i],i=1..m)], z, form=Lagrange ):
W9:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[9,i],i=1..m)], z, form=Lagrange ):
plot([W1, W2, W3, W4, W5, W6, W7, W8, W9],
z=1..m, color=[aquamarine, black, blue, navy,
coral, cyan, brown, gold, green],
thickness=[2, 2, 2, 2, 2, 2, 2, 2, 2],
legend=[`1`, `2`,
`3`, `4`, `5`, `6`, `7`, `8`, `9`]);
> for i from 1 to n do 
W3:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[3,i],i=1..m)], z, form=Lagrange ):
W4:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[4,i],i=1..m)], z, form=Lagrange ):
W5:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[5,i],i=1..m)], z, form=Lagrange ):
W6:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[6,i],i=1..m)], z, form=Lagrange ):
W7:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[7,i],i=1..m)], z, form=Lagrange ):
W8:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[8,i],i=1..m)], z, form=Lagrange ):
W9:=PolynomialInterpolation([seq(i, i=1..m)],
[seq(X[9,i],i=1..m)], z, form=Lagrange ):
plot([W1, W2, W3, W4, W5, W6, W7, W8, W9],
z=1..m, color=[aquamarine, black, blue, navy,
        coral, cyan, brown, gold, green],
thickness=[2, 2, 2, 2, 2, 2, 2, 2, 2],
legend=[`1`, `2`,
        `3`, `4`, `5`, `6`, `7`, `8`, `9`]);




>   for i from 1 to n do
                           44

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