Thanks for your answer.
But I really want to know whether I can get "Residual Standard Error",
directly. If I use summary(), there is an item "Residual Standard
Error". So I think we might can access this information directly.
Thanks again,
> summary(mod)
Call:
loess(formula = y ~ x)
Number of Observations: 10
Equivalent Number of Parameters: 4.95
Residual Standard Error: 8.734e-16
Trace of smoother matrix: 5.47
Control settings:
normalize: TRUE
span : 0.75
degree : 2
family : gaussian
surface : interpolate cell = 0.2
>>> Douglas Bates <bates at stat.wisc.edu> 12/13/02 04:15PM
>>>
"Zhongming Yang" <Zhongming.Yang at cchmc.org> writes:
> Hi,
>
> I use lm or loess to make smoothing. After smoothing I need
"Residual> Standard Error" in my script. Could you please tell me how can I get
> this information?
A preferred way would be to use
sqrt(deviance(fm)/df.residual(fm))
if fm is your fitted model.
pFor example
> data(Formaldehyde)
> fm <- lm(optden ~ carb, data = Formaldehyde)
> summary(fm)
Call:
lm(formula = optden ~ carb, data = Formaldehyde)
Residuals:
1 2 3 4 5 6
-0.006714 0.001029 0.002771 0.007143 0.007514 -0.011743
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.005086 0.007834 0.649 0.552
carb 0.876286 0.013535 64.744 3.41e-07 ***
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` '
1
Residual standard error: 0.008649 on 4 degrees of freedom
Multiple R-Squared: 0.999, Adjusted R-squared: 0.9988
F-statistic: 4192 on 1 and 4 DF, p-value: 3.409e-07
> sqrt(deviance(fm)/df.residual(fm))
[1] 0.0086487
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