南京理工大学-吴健误差实验报告

1、Matlab分析报告>> y=162,175,162,156,174,157,154,177,159,171,166,162,171,183,163,152,165,175,167,170,170,167,171,164,163,170,164,162,167,166,153,173,158,174,170,167,157,178,163,163,158,154,149,178,160,164,160,171,153,178,160,155,169,165,161,166,169,172,169,161,163,171,171,163,171,165,159,161,157,161

2、,175,151,164,180,162,153,182,158,166,178,169,161,174,155,165,167,165,165,169,165,162,151,171,169,157,173,163,161,168,152;>> m=ar(y,1,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 - 0.9969 z-1 Sample time: 1 seconds Parameterization:Polynomial orders: na=1 Number o

3、f free coefficients: 1 Use "polydata", "getpvec", "getcov" for parameters and their uncertainties.Status: Estimated using AR ('ls/now') on "y". Fit to estimation data: -57.67% (prediction focus)FPE: 142.6, MSE: 139.8 >> a=aic(m)a = 4.9602 >>

4、; m=ar(y,2,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 - 0.4527 z-1 - 0.5449 z-2 Sample time: 1 seconds Parameterization:Polynomial orders: na=2 Number of free coefficients: 2 Use "polydata", "getpvec", "getcov" for parameters and their u

5、ncertainties.Status: Estimated using AR ('ls/now') on "y". Fit to estimation data: -31.46% (prediction focus)FPE: 102.1, MSE: 97.19 >> m=ar(y,3,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 - 0.1406 z-1 - 0.2743 z-2 - 0.5836 z-3 Sample time: 1 se

6、conds Parameterization:Polynomial orders: na=3 Number of free coefficients: 3 Use "polydata", "getpvec", "getcov" for parameters and their uncertainties.Status: Estimated using AR ('ls/now') on "y". Fit to estimation data: -6.636% (prediction focus)FPE

7、: 69.18, MSE: 63.95 >> m=ar(y,4,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 + 0.02995 z-1 - 0.2106 z-2 - 0.5388 z-3 - 0.2797 z-4 Sample time: 1 seconds Parameterization:Polynomial orders: na=4 Number of free coefficients: 4 Use "polydata", "getpve

8、c", "getcov" for parameters and their uncertainties.Status: Estimated using AR ('ls/now') on "y". Fit to estimation data: -1.623% (prediction focus)FPE: 64.69, MSE: 58.08 >> m=ar(y,5,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 +

9、0.03727 z-1 - 0.1853 z-2 - 0.5206 z-3 - 0.2799 z-4 - 0.05023 z-5 Sample time: 1 seconds Parameterization:Polynomial orders: na=5 Number of free coefficients: 5 Use "polydata", "getpvec", "getcov" for parameters and their uncertainties.Status: Estimated using AR ('ls

10、/now') on "y". Fit to estimation data: -1.269% (prediction focus)FPE: 66.11, MSE: 57.67 >> m=ar(y,6,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 + 0.04687 z-1 - 0.0444 z-2 - 0.2881 z-3 - 0.216 z-4 - 0.06591 z-5 - 0.4317 z-6 Sample time: 1 seconds Pa

11、rameterization:Polynomial orders: na=6 Number of free coefficients: 6 Use "polydata", "getpvec", "getcov" for parameters and their uncertainties.Status: Estimated using AR ('ls/now') on "y". Fit to estimation data: 8.998% (prediction focus)FPE: 54.94,

12、MSE: 46.57 >> m=ar(y,7,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 + 0.004583 z-1 - 0.05691 z-2 - 0.3041 z-3 - 0.2516 z -4 - 0.0821 z-5 - 0.4265 z-6 + 0.1169 z-7 Sample time: 1 seconds Parameterization:Polynomial orders: na=7 Number of free coefficients: 7 Use &

13、quot;polydata", "getpvec", "getcov" for parameters and their uncertainties.Status: Estimated using AR ('ls/now') on "y". Fit to estimation data: 10.24% (prediction focus)FPE: 54.98, MSE: 45.31 >> m=ar(y,8,'ls');>> mm =Discrete-time AR mo

14、del: A(z)y(t) = e(t) A(z) = 1 - 0.03306 z-1 + 0.02715 z-2 - 0.2851 z-3 - 0.2032 z-4 - 0.009981 z-5 - 0.405 z-6 + 0.1232 z-7 - 0.2133 z-8 Sample time: 1 seconds Parameterization:Polynomial orders: na=8 Number of free coefficients: 8 Use "polydata", "getpvec", "getcov" fo

15、r parameters and their uncertainties.Status: Estimated using AR ('ls/now') on "y". Fit to estimation data: 12.91% (prediction focus)FPE: 53.24, MSE: 42.65 >> m=ar(y,9,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 - 0.008939 z-1 + 0.01462 z-2 - 0.

16、2107 z-3 - 0.2055 z -4 + 0.02893 z-5 - 0.3586 z-6 + 0.1147 z-7 - 0.212 z-8 - 0.1619 z-9 Sample time: 1 seconds Parameterization:Polynomial orders: na=9 Number of free coefficients: 9 Use "polydata", "getpvec", "getcov" for parameters and their uncertainties.Status: Esti

17、mated using AR ('ls/now') on "y". Fit to estimation data: 14.14% (prediction focus)FPE: 53.22, MSE: 41.46 >> m=ar(y,10,'ls');>> mm =Discrete-time AR model: A(z)y(t) = e(t) A(z) = 1 - 0.001623 z-1 + 0.0573 z-2 - 0.2452 z-3 - 0.1783 z-4 + 0.03254 z-5 - 0.3499 z-6

18、+ 0.1506 z-7 - 0.2021 z-8 - 0.149 z-9 - 0.113 z-10 Sample time: 1 seconds Parameterization:Polynomial orders: na=10 Number of free coefficients: 10 Use "polydata", "getpvec", "getcov" for parameters and their uncertainties.Status: Estimated using AR ('ls/now') on "