回归模型公式
Xdegree=1,Ydegree=1
Linear model Poly11:
f(x,y) = p00 + p10*x + p01*y
Coefficients (with 95% confidence bounds):
p00 = 41.68(40.59, 42.76)
p10 = -0.001093(-0.005824, 0.003638)
p01 = -0.04824(-0.05297, -0.04351)
Xdegree=1,Ydegree=2
Linear model Poly12:
f(x,y) = p00 + p10*x + p01*y + p11*x*y + p02*y^2
Coefficients (with 95% confidence bounds):
p00 = 14.87(13.08, 16.66)
p10 = -0.1091(-0.1181, -0.1001)
p01 = 0.6992(0.6796, 0.7188)
p11 = 0.0007174(0.0006656, 0.0007692)
p02 = -0.002842(-0.0029, -0.002784)
Xdegree=2,Ydegree=1
Linear model Poly21:
f(x,y) = p00 + p10*x + p01*y + p20*x^2 + p11*x*y
Coefficients (with 95% confidence bounds):
p00 = 47.66(45.79, 49.54)
p10 = 0.09484(0.07428, 0.1154)
p01 = -0.1562(-0.1656, -0.1468)
p20 =-0.0006774(-0.0007381, -0.0006167)
p11 = 0.0007174(0.0006631, 0.0007717)
Xdegree=2,Ydegree=2
Linear model Poly22:
f(x,y) = p00 + p10*x + p01*y + p20*x^2 + p11*x*y + p02*y^2
Coefficients (with 95% confidence bounds):
p00 = 4.609(2.619, 6.599)
p10 = 0.09484(0.07527, 0.1144)
p01 = 0.6992(0.6796, 0.7188)
p20 =-0.0006774(-0.0007352, -0.0006196)
p11 = 0.0007174(0.0006657, 0.0007691)
p02 = -0.002842(-0.0029, -0.002784)
B站视频:MATLAB线性拟合工具箱使用
https://www.bilibili.com/video/BV1pt4y1H7BE?spm_id_from=333.999.0.0
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