[R]Copula in R?
Thomas Holm
thomas at holm.cn
Thu Nov 6 22:08:26 CET 2003
Is there any function to mesure different copulas in R?
Would appreciate any codes or whatever information you may have.
Thank you in advance
Thomas Holm
thomas at holm.cn
-----Ursprungligt meddelande-----
Från: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] För JB
Skickat: den 6 november 2003 22:51
Till: R-help at stat.math.ethz.ch
Ämne: [R] newbie's additional (probably to some extent OT) questions
(1)
So finally, thank to your help I have this:
summary(lm(x ~ 0+I(t^2)))
And then I get this result:
=================================================
Call:
lm(formula = x ~ 0 + I(t^2))
Residuals:
Min 1Q Median 3Q Max
-3.332e-02 -9.362e-03 1.169e-05 1.411e-02 3.459e-02
Coefficients:
Estimate Std. Error t value Pr(>|t|)
I(t^2) 0.0393821 0.0001487 264.8 <2e-16 ***
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
Residual standard error: 0.01945 on 18 degrees of freedom
Multiple R-Squared: 0.9997, Adjusted R-squared: 0.9997
F-statistic: 7.014e+04 on 1 and 18 DF, p-value: < 2.2e-16
=================================================
I see in MuPad, that Delta^2 is 0.006813. Now is not the standard error
the
square root of Delta^2? Should I not get 0.069 as standard error?
(2)
When I use the model
summary(lm(x ~ I(t^2)))
I get (of course) another result with a slightly smaller Delta^2. But I
do
not expect such an error as this would mean that there was a systematic
error in our measurement of the distance and if I understand the result
of
R correctly, the error was 0.04m which is impossible:
==========================================================
Call:
lm(formula = x ~ I(t^2))
Residuals:
Min 1Q Median 3Q Max
-0.0202520 -0.0116533 -0.0006036 0.0036699 0.0432987
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0427606 0.0161085 2.655 0.0167 *
I(t^2) 0.0379989 0.0005367 70.801 <2e-16 ***
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
Residual standard error: 0.01683 on 17 degrees of freedom
Multiple R-Squared: 0.9966, Adjusted R-squared: 0.9964
F-statistic: 5013 on 1 and 17 DF, p-value: < 2.2e-16
=====================================================
What is going on here?
(Sorry but I am only a high school teacher and have not much idea of
statistics.)
TIA,
JB
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