个因素与时间拟合图.docx
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个因素与时间拟合图.docx
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个因素与时间拟合图
城镇居民人均可支配收入与时间图的结果值:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=1149(931.4,1366)
p2=-2.292e+006(-2.727e+006,-1.856e+006)
Goodnessoffit:
SSE:
3.544e+006
R-square:
0.9571
AdjustedR-square:
0.951
RMSE:
711.5
税收与时间图的结果值:
LinearmodelPoly2:
f(x)=p1*x^2+p2*x+p3
Coefficients(with95%confidencebounds):
p1=347.3(289.5,405.1)
p2=-1.387e+006(-1.618e+006,-1.155e+006)
p3=1.384e+009(1.152e+009,1.615e+009)
Goodnessoffit:
SSE:
5.314e+007
R-square:
0.9903
AdjustedR-square:
0.9888
RMSE:
2022
人均GDP占有量与时间图的结果值:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=1746(1341,2152)
p2=-3.486e+006(-4.299e+006,-2.673e+006)
Goodnessoffit:
SSE:
1.236e+007
R-square:
0.9367
AdjustedR-square:
0.9277
RMSE:
1329
城市化率与时间图的结果值:
Generalmodel:
f(x)=a*x+b
Coefficients(with95%confidencebounds):
a=1.283(1.136,1.43)
b=-2530(-2824,-2237)
Goodnessoffit:
SSE:
37.15
R-square:
0.9555
AdjustedR-square:
0.9527
RMSE:
1.524
GDP时间图计算结果:
LinearmodelPoly2:
f(x)=p1*x^2+p2*x+p3
Coefficients(with95%confidencebounds):
p1=1174(858.6,1489)
p2=-4.68e+006(-5.94e+006,-3.419e+006)
p3=4.664e+009(3.403e+009,5.925e+009)
Goodnessoffit:
SSE:
3.388e+009
R-square:
0.9774
AdjustedR-square:
0.9744
RMSE:
1.503e+004
贷款利率与时间图计算结果:
LinearmodelPoly4:
f(x)=p1*x^4+p2*x^3+p3*x^2+p4*x+p5
Coefficients(with95%confidencebounds):
p1=-0.002333(-0.003327,-0.001339)
p2=18.68(10.73,26.63)
p3=-5.609e+004(-7.995e+004,-3.223e+004)
p4=7.485e+007(4.303e+007,1.067e+008)
p5=-3.746e+010(-5.338e+010,-2.154e+010)
Goodnessoffit:
SSE:
11.26
R-square:
0.9311
AdjustedR-square:
0.9099
RMSE:
0.9307
汇率与时间图计算结果:
LinearmodelPoly3:
f(x)=p1*x^3+p2*x^2+p3*x+p4
Coefficients(with95%confidencebounds):
p1=-0.2348(-0.308,-0.1616)
p2=1409(969.2,1848)
p3=-2.817e+006(-3.697e+006,-1.938e+006)
p4=1.878e+009(1.291e+009,2.465e+009)
Goodnessoffit:
SSE:
1229
R-square:
0.9659
AdjustedR-square:
0.9574
RMSE:
10.12
土地交易价格与时间图计算结果:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=127.1(108,146.2)
p2=-2.529e+005(-2.912e+005,-2.146e+005)
Goodnessoffit:
SSE:
7.079e+004
R-square:
0.9617
AdjustedR-square:
0.9574
RMSE:
88.69
房价与时间图计算结果:
LinearmodelPoly3:
f(x)=p1*x^3+p2*x^2+p3*x+p4
Coefficients(with95%confidencebounds):
p1=1.543(0.8945,2.191)
p2=-9250(-1.314e+004,-5359)
p3=1.849e+007(1.07e+007,2.627e+007)
p4=-1.232e+010(-1.751e+010,-7.126e+009)
Goodnessoffit:
SSE:
2.677e+005
R-square:
0.9839
AdjustedR-square:
0.9805
RMSE:
138.3
人均居住用地面积(m^2)与时间拟合结果:
jm=[53.5
52.4
51.5
49.9
55.6
47
55.7
36.1
50.2
51.6
];
>>t=[1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
];
>>cftool
>>
住宅用地年供应量(亿m^2)与时间拟合结果:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=0.287(0.2496,0.3244)
p2=-568.9(-643.8,-494.1)
Goodnessoffit:
SSE:
2.415
R-square:
0.943
AdjustedR-square:
0.9394
RMSE:
0.3885
住房保障比例与时间拟合结果:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=-4.038(-5.173,-2.903)
p2=8132(5858,1.041e+004)
Goodnessoffit:
SSE:
96.72
R-square:
0.91
AdjustedR-square:
0.8972
RMSE:
3.717
恩格尔系数随时间拟合结果:
LinearmodelPoly3:
f(x)=p1*x^3+p2*x^2+p3*x+p4
Coefficients(with95%confidencebounds):
p1=0.007723(0.002588,0.01286)
p2=-46.28(-77.09,-15.46)
p3=9.244e+004(3.08e+004,1.541e+005)
p4=-6.155e+007(-1.027e+008,-2.044e+007)
Goodnessoffit:
SSE:
16.79
R-square:
0.973
AdjustedR-square:
0.9672
RMSE:
1.095
人均住宅消费支出(元)随时间拟合结果:
LinearmodelPoly2:
f(x)=p1*x^2+p2*x+p3
Coefficients(with95%confidencebounds):
p1=3.265(1.812,4.717)
p2=-1.301e+004(-1.883e+004,-7190)
p3=1.296e+007(7.131e+006,1.879e+007)
Goodnessoffit:
SSE:
8509
R-square:
0.9907
AdjustedR-square:
0.9888
RMSE:
29.17
房地产开发企业本年完成投资额(亿元)与时间:
LinearmodelPoly3:
f(x)=p1*x^3+p2*x^2+p3*x+p4
Coefficients(with95%confidencebounds):
p1=12.77(10.71,14.82)
p2=-7.643e+004(-8.878e+004,-6.407e+004)
p3=1.525e+008(1.278e+008,1.772e+008)
p4=-1.015e+011(-1.179e+011,-8.499e+010)
Goodnessoffit:
SSE:
2.699e+006
R-square:
0.9986
AdjustedR-square:
0.9983
RMSE:
439
造价费用(元/m^2)与时间:
LinearmodelPoly4:
f(x)=p1*x^4+p2*x^3+p3*x^2+p4*x+p5
Coefficients(with95%confidencebounds):
p1=-0.3928(-0.5193,-0.2663)
p2=3145(2133,4158)
p3=-9.445e+006(-1.248e+007,-6.406e+006)
p4=1.26e+010(8.55e+009,1.666e+010)
p5=-6.307e+012(-8.335e+012,-4.279e+012)
Goodnessoffit:
SSE:
4815
R-square:
0.9905
AdjustedR-square:
0.9858
RMSE:
24.53
房价随GDP拟合结果:
LinearmodelPoly2:
f(x)=p1*x^2+p2*x+p3
Coefficients(with95%confidencebounds):
p1=-1.042e-008(-2.074e-008,-1.031e-010)
p2=0.01412(0.01032,0.01792)
p3=790.1(522,1058)
Goodnessoffit:
SSE:
3.892e+005
R-square:
0.9766
AdjustedR-square:
0.9735
RMSE:
161.1
房价随城镇居民家庭人均可支配收入(元)拟合结果:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=0.221(0.203,0.2391)
p2=691(529.3,852.7)
Goodnessoffit:
SSE:
3.869e+005
R-square:
0.9768
AdjustedR-square:
0.9753
RMSE:
155.5
房价随城市化率拟合结果:
LinearmodelPoly3:
f(x)=p1*x^3+p2*x^2+p3*x+p4
Coefficients(with95%confidencebounds):
p1=2.055(1.492,2.618)
p2=-221.7(-284.9,-158.5)
p3=7970(5636,1.03e+004)
p4=-9.317e+004(-1.214e+005,-6.493e+004)
Goodnessoffit:
SSE:
3.006e+005
R-square:
0.982
AdjustedR-square:
0.9781
RMSE:
146.5
房价随贷款利率拟合结果:
房价随人均GDP占有量(元/人)拟合结果:
LinearmodelPoly2:
f(x)=p1*x^2+p2*x+p3
Coefficients(with95%confidencebounds):
p1=-3.392e-006(-5.547e-006,-1.236e-006)
p2=0.2269(0.1742,0.2796)
p3=557.7(291.1,824.2)
Goodnessoffit:
SSE:
2.583e+005
R-square:
0.9771
AdjustedR-square:
0.9738
RMSE:
135.8
房价随汇率拟合结果:
LinearmodelPoly5:
f(x)=p1*x^5+p2*x^4+p3*x^3+p4*x^2+p5*x+p6
Coefficients(with95%confidencebounds):
p1=2.36e-006(8.409e-007,3.878e-006)
p2=-0.009059(-0.01492,-0.003202)
p3=13.88(4.863,22.9)
p4=-1.061e+004(-1.754e+004,-3684)
p5=4.048e+006(1.392e+006,6.704e+006)
p6=-6.162e+008(-1.023e+009,-2.097e+008)
Goodnessoffit:
SSE:
4.8e+005
R-square:
0.9628
AdjustedR-square:
0.9442
RMSE:
219.1
房价随税收收入合计(亿元)拟合结果:
LinearmodelPoly2:
f(x)=p1*x^2+p2*x+p3
Coefficients(with95%confidencebounds):
p1=-1.665e-007(-5.243e-007,1.912e-007)
p2=0.05855(0.03481,0.0823)
p3=1362(1086,1637)
Goodnessoffit:
SSE:
4.342e+005
R-square:
0.9664
AdjustedR-square:
0.9612
RMSE:
182.8
房价随土地交易价格(元)拟合结果:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=0.007566(0.006427,0.008704)
p2=1990(1988,1992)
Goodnessoffit:
SSE:
4.213
R-square:
0.9617
AdjustedR-square:
0.9574
RMSE:
0.6842
房价随造价费用(元/m^2)拟合结果:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=3.141(2.633,3.65)
p2=-1530(-2179,-882.1)
Goodnessoffit:
SSE:
2.992e+005
R-square:
0.9438
AdjustedR-square:
0.9387
RMSE:
164.9
房价随房地产开发企业本年完成投资额(亿元)拟合结果:
LinearmodelPoly2:
f(x)=p1*x^2+p2*x+p3
Coefficients(with95%confidencebounds):
p1=-1.301e-006(-2.538e-006,-6.403e-008)
p2=0.1333(0.08976,0.1769)
p3=1289(1046,1532)
Goodnessoffit:
SSE:
8.281e+005
R-square:
0.9503
AdjustedR-square:
0.9437
RMSE:
235
房价随住房保障比例拟合结果:
LinearmodelPoly1:
f(x)=p1*x+p2
Coefficients(with95%confidencebounds):
p1=-62.68(-72.85,-52.5)
p2=5386(4984,5788)
Goodnessoffit:
SSE:
2.626e+005
R-square:
0.9618
AdjustedR-square:
0.9571
RMSE:
181.2
房价随住宅用地年供应量(亿m^2)拟合结果:
LinearmodelPoly6:
f(x)=p1*x^6+p2*x^5+p3*x^4+p4*x^3+p5*x^2+
p6*x+p7
Coefficients(with95%confidencebounds):
p1=10.68(-0.7604,22.12)
p2=-341.6(-705.8,22.64)
p3=4410(-295.8,9117)
p4=-2.932e+004(-6.085e+004,2199)
p5=1.056e+005(-9574,2.207e+005)
p6=-1.942e+005(-4.111e+005,2.258e+004)
p7=1.433e+005(-2.049e+004,3.071e+005)
Goodnessoffit:
SSE:
8.043e+005
R-square:
0.9517
AdjustedR-square:
0.9254
RMSE:
270.4
房价随恩格尔系数(%)拟合结果:
GeneralmodelGauss3:
f(x)=
a1*exp(-((x-b1)/c1)^2)+a2*exp(-((x-b2)/c2)^2)+
a3*exp(-((x-b3)/c3)^2)
Coefficients(with95%confidencebounds):
a1=2643(1426,3859)
b1=36.26(36.12,36.4)
c1=0.6962(0.3512,1.041)
a2=1941(777.9,3104)
b2=37.92(37.81,38.02)
c2=0.2014(0.06613,0.3368)
a3=2168(1755,2580)
b3=42.59(38.1,47.08)
c3=12.04(3.99,20.09)
Goodnessoffit:
SSE:
9.078e+005
R-square:
0.9455
AdjustedR-square:
0.8971
RMSE:
317.6
房价随人均住宅消费支出(元)拟合结果:
LinearmodelPoly2:
f(x)=p1*x^2+p2*x+p3
Coefficients(with95%confidencebounds):
p1=0.001876(-0.0001569,0.003909)
p2=0.1117(-3.127,3.35)
p3=1608(431.2,2786)
Goodnessoffit:
SSE:
4.893e+005
R-square:
0.9471
AdjustedR-square:
0.9365
RMSE:
221.2
人均居住用地面积:
clear
clc
x1=[1345.43
1418.31
1462.72
1584.12
1744.12
1902.84
2013.2
2260.82
2474
];
x2=[7858
8622
9398
10542
12336
14040
15931
18268
22675
];
x3=[36.22
37.66
39.09
40.53
41.76
42.99
43.9
44.94
45.68
];
x4=[6280
6859.6
7702.8
8472.2
9421.6
10493
11759.5
13785.8
15780.76
];
x5=[50.51
50.84
49.77
47.36
43.57
38.98
33
25.96
19.08
];
x=[ones(9,1),x1,x2,x3,x4,x5,x1.*x2,x4.^x5];
y=[2111.6
2169.7
2250.2
2359.5
2713.9
3167.7
3366.8
3
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- 因素 时间 拟合