Mathematica的数值模拟法计算具体问题为:通过两个数据二次线性回归y=b0+b1x+b2x^2测得二次项系数b2,标准差Sb2,;如何用数值模拟法测出y或Sx对b2/Sb2的影响有多大就是有个源代码给我发过来也好
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![Mathematica的数值模拟法计算具体问题为:通过两个数据二次线性回归y=b0+b1x+b2x^2测得二次项系数b2,标准差Sb2,;如何用数值模拟法测出y或Sx对b2/Sb2的影响有多大就是有个源代码给我发过来也好](/uploads/image/z/13447942-70-2.jpg?t=Mathematica%E7%9A%84%E6%95%B0%E5%80%BC%E6%A8%A1%E6%8B%9F%E6%B3%95%E8%AE%A1%E7%AE%97%E5%85%B7%E4%BD%93%E9%97%AE%E9%A2%98%E4%B8%BA%EF%BC%9A%E9%80%9A%E8%BF%87%E4%B8%A4%E4%B8%AA%E6%95%B0%E6%8D%AE%E4%BA%8C%E6%AC%A1%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92y%3Db0%2Bb1x%2Bb2x%5E2%E6%B5%8B%E5%BE%97%E4%BA%8C%E6%AC%A1%E9%A1%B9%E7%B3%BB%E6%95%B0b2%2C%E6%A0%87%E5%87%86%E5%B7%AESb2%2C%EF%BC%9B%E5%A6%82%E4%BD%95%E7%94%A8%E6%95%B0%E5%80%BC%E6%A8%A1%E6%8B%9F%E6%B3%95%E6%B5%8B%E5%87%BAy%E6%88%96Sx%E5%AF%B9b2%2FSb2%E7%9A%84%E5%BD%B1%E5%93%8D%E6%9C%89%E5%A4%9A%E5%A4%A7%E5%B0%B1%E6%98%AF%E6%9C%89%E4%B8%AA%E6%BA%90%E4%BB%A3%E7%A0%81%E7%BB%99%E6%88%91%E5%8F%91%E8%BF%87%E6%9D%A5%E4%B9%9F%E5%A5%BD)
Mathematica的数值模拟法计算具体问题为:通过两个数据二次线性回归y=b0+b1x+b2x^2测得二次项系数b2,标准差Sb2,;如何用数值模拟法测出y或Sx对b2/Sb2的影响有多大就是有个源代码给我发过来也好
Mathematica的数值模拟法计算
具体问题为:
通过两个数据二次线性回归y=b0+b1x+b2x^2测得二次项系数b2,标准差Sb2,;如何用数值模拟法测出y或Sx对b2/Sb2的影响有多大
就是有个源代码给我发过来也好 我看着改一改
Mathematica的数值模拟法计算具体问题为:通过两个数据二次线性回归y=b0+b1x+b2x^2测得二次项系数b2,标准差Sb2,;如何用数值模拟法测出y或Sx对b2/Sb2的影响有多大就是有个源代码给我发过来也好
tV1 = {};
tV2 = {};
tdata1 = {.003394511,.003350113,.003298160,.003245895,.003180386,\
.003114193,.003053291,.002968749,.002944187,.002900259,\
.002868830,.002809518,.002779967,.002761163};
tdata2 = {.003394511,.003350113,.003298160,.003245895,.003180386,\
.003114193,.003053291,.002968749,.002944187,.002900259,\
.002868830,.002809518,.002779967,.002761163};
Vdata2 = {8.651024539,8.488999457,8.305484018,8.119696253,
7.893572074,7.654443226,7.420578905,7.166265974,7.064759028,
6.887552572,6.763884909,6.570882962,6.415096959,6.340359304};
i = 14;
While[i >= 1,AppendTo[tV1,{tdata1[[i]],Vdata2[[i]]}]; i = i - 1];
Print["实验结果数据组:"]
tV1
g1 = ListPlot[tV1,AxesOrigin -> {0.0027,6.3},
PlotStyle -> {Red,PointSize[0.02]}];
tV1 = Fit[tV1,{1,t},t];
g2 = Plot[tV1,{t,0.00275,.0034},PlotStyle -> {Blue}];
Print["实验结果点分布和拟合效果图"]
Show[g1,g2]
Print["实验拟合公式:"]
tV1
b01 = tV1[[1]];
b11 = tV1[[2]]/t;
i = 14;
Print[]
Print["温度项加入-0.000005~0.000005度的随机误差,模拟读温度时的不确定性"]
While[i >= 1,
tdata2[[i]] = tdata2[[i]] + .00001 RandomReal[] - 0.000005;
i = i - 1];
tsb = 0;
i = 14;
While[i >= 1,tsb = tsb + (tdata2[[i]] - tdata1[[i]])^2; i = i - 1];
tsb = Sqrt[tsb/14];
i = 14;
While[i >= 1,AppendTo[tV2,{tdata2[[i]],Vdata2[[i]]}]; i = i - 1];
Print[]
Print["模拟结果数据组:"]
tV2
g3 = ListPlot[tV2,AxesOrigin -> {0.0027,6.3},
PlotStyle -> {Green,PointSize[0.02]}];
tV2 = Fit[tV2,{1,t},t];
g4 = Plot[tV2,{t,0.00275,.0034},PlotStyle -> {Orange}];
Print["模拟结果点分布和拟合效果图"]
Show[g3,g4]
Print["模拟后拟合公式:"]
tV2
b02 = tV2[[1]];
b12 = tV2[[2]]/t;
Show[g1,g2,g3,g4]
Print["模拟截距"]
Print[b02]
Print["模拟斜率"]
Print[b12]