Теория массового обслуживания. Сивохин А.В - 185 стр.

UptoLike

185
]
> Lp4:=[seq(rhs(Lpi[t][5]), t=0..7)];
Lp4 := [0., 0.0129438608656616324, 0.0188454668683919364, 0.0199089714127403186,
0.0200847947882790631, 0.0201191280174715312, 0.0201191807088391406, 0.0201191510889340460
]
> Lp5:=[seq(rhs(Lpi[t][6]), t=0..7)];
Lp5 := [0., 0.00167170540396938390, 0.00278474601738116884, 0.00299784582794319172,
0.00303334593017586972, 0.00304029476583665042, 0.00304027559899271117,
0.00304028620131242475]
> listplot([seq(Lp1[t], t=1..8)], thickness=2,
color= green, legend=`p0(t)`);
plot(PolynomialInterpolation([seq(t, t=1..8)],
[seq(Lp1[t], t=1..8)], z, form=Lagrange ),
z=1..8,
thickness=2, color= red,
legend=`p0(t)`);
     ]

>   Lp4:=[seq(rhs(Lpi[t][5]), t=0..7)];
Lp4 := [0., 0.0129438608656616324, 0.0188454668683919364, 0.0199089714127403186,
     0.0200847947882790631, 0.0201191280174715312, 0.0201191807088391406, 0.0201191510889340460
     ]

>   Lp5:=[seq(rhs(Lpi[t][6]), t=0..7)];
         Lp5 := [0., 0.00167170540396938390, 0.00278474601738116884, 0.00299784582794319172,
              0.00303334593017586972, 0.00304029476583665042, 0.00304027559899271117,
              0.00304028620131242475]

> listplot([seq(Lp1[t], t=1..8)], thickness=2,
color= green, legend=`p0(t)`);
plot(PolynomialInterpolation([seq(t, t=1..8)],
[seq(Lp1[t], t=1..8)], z, form=Lagrange ),
z=1..8,
           thickness=2, color= red,
legend=`p0(t)`);




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