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Fit y ~ 3 - 2 x + 0.05 * sin(x) model using 20 points (sin(x) ~ noise)
Basis( [[v0]->[1],[v0]->[v0]] )
Coefficients:
| Estimate | Std Error | t value | Pr(>|t|) |
--------------------------------------------------------------------
[v0]->[1] | 3.01168 | 0.00922587 | 326.438 | 2.07338e-35 |
[v0]->[v0] | -2.00025 | 0.00176374 | -1134.1 | 3.81897e-45 |
--------------------------------------------------------------------
Residual standard error: 0.037647 on 18 degrees of freedom
F-statistic: 1.2862e+06 , p-value: 0
---------------------------------
Multiple R-squared | 0.999986 |
Adjusted R-squared | 0.999985 |
---------------------------------
-----------------------------------
Normality test | p-value |
-----------------------------------
Anderson-Darling | 0.00258386 |
Cramer-Von Mises | 0.00392808 |
Chi-Squared | 0.157724 |
Kolmogorov-Smirnov | 0.17747 |
-----------------------------------
confidence intervals with level=0.95 : [2.99229, 3.03106]
[-2.00396, -1.99655]
Fit y ~ 1 + 0.1 x + 10 x^2 model using 100 points
Basis( [[v0,v1]->[1],[v0,v1]->[v0],[v0,v1]->[v1]] )
Coefficients:
| Estimate | Std Error | t value | Pr(>|t|) |
---------------------------------------------------------------------------
[v0,v1]->[1] | 0.978992 | 0.0292861 | 33.4285 | 4.90736e-55 |
[v0,v1]->[v0] | 0.110565 | 0.0135353 | 8.16865 | 1.17433e-12 |
[v0,v1]->[v1] | 9.99924 | 0.00130974 | 7634.54 | 4.32412e-282 |
---------------------------------------------------------------------------
Residual standard error: 0.099579 on 97 degrees of freedom
F-statistic: 4.5871e+08 , p-value: 0
--------------------------
Multiple R-squared | 1 |
Adjusted R-squared | 1 |
--------------------------
---------------------------------
Normality test | p-value |
---------------------------------
Anderson-Darling | 0.57332 |
Cramer-Von Mises | 0.535457 |
Chi-Squared | 0.783691 |
Kolmogorov-Smirnov | 0.821849 |
---------------------------------
confidence intervals with level=0.95 : [0.920867, 1.03712]
[0.0837015, 0.137429]
[9.99664, 10.0018]
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