R version 3.6.1 (2019-07-05) -- "Action of the Toes"
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> ## testing stdEr() methods
> library( "miscTools" )
> data( "cars" )
>
> # lm()
> lmRes <- lm(dist ~ speed, data=cars)
> summary( lmRes )
Call:
lm(formula = dist ~ speed, data = cars)
Residuals:
Min 1Q Median 3Q Max
-29.069 -9.525 -2.272 9.215 43.201
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -17.5791 6.7584 -2.601 0.0123 *
speed 3.9324 0.4155 9.464 1.49e-12 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 15.38 on 48 degrees of freedom
Multiple R-squared: 0.6511, Adjusted R-squared: 0.6438
F-statistic: 89.57 on 1 and 48 DF, p-value: 1.49e-12
> round( stdEr( lmRes ), 4 )
(Intercept) speed
6.7584 0.4155
>
> # nls()
> nlsRes <- nls( dist ~ b0 + b1 * speed^b2, start = c( b0=0, b1=1, b2=1 ),
+ data = cars )
> tmp <- summary( nlsRes )
> tmp$convInfo$finTol <- round( tmp$convInfo$finTol, 4 )
> print( tmp )
Formula: dist ~ b0 + b1 * speed^b2
Parameters:
Estimate Std. Error t value Pr(>|t|)
b0 5.4878 10.6846 0.514 0.60992
b1 0.2612 0.4847 0.539 0.59248
b2 1.7875 0.5553 3.219 0.00233 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 15.19 on 47 degrees of freedom
Number of iterations to convergence: 7
Achieved convergence tolerance: 0
> round( stdEr( nlsRes ), 3 )
b0 b1 b2
10.685 0.485 0.555
>
> proc.time()
user system elapsed
0.118 0.032 0.143
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