lin1_theta: Candidate point evaluation for simplicial depth in the linear...
In ChrisKust/rexpar: Simplicial Depth for Explosive Autoregressive Processes
Description
Usage
Arguments
Value
Author(s)
References
See Also
Examples
Description
This function precalculates parameters on which depth changes to restirict the
region on which the depht statistic has to be evaluated on as described in Kustosz and Mueller(2014).
Usage
1
lin1_theta(dat)
Arguments
dat
Data from an AR(1) Model without intercept
Value
t1
Candidate values for theta1
t2
Candidate values for theta2
Author(s)
Kustosz, Christoph
References
Kustosz, C. (2016). Depth based estimators and tests for
autoregressive processes with application. Ph. D. thesis. TU Dortmund.
Kustosz C., Mueller Ch. H. and Wendler M. (2016). Simplified Simplicial Depth for Regression and
Autoregressive Growth Processes. Journal of Statistical Planning and Inference. In press.
Kustosz C. and Mueller Ch. H. (2014). Analysis of crack growth with robust distribution-
free estimators and tests for nonstationary autoregressive processes. Statistical
Papers 55, 125-140.
See Also
dS_lin2,dS1_lin2,dS2_lin2,dS3_lin2, lin2_CI,est_lin2,est_nlin1
Examples
1
2
3
y <- RandomARMod_lin2(100, 1.001, 0, 15, "0")
thetas <- lin1_theta(y)
summary(thetas$t1)
ChrisKust/rexpar documentation built on May 6, 2019, 11:48 a.m.
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Description Usage Arguments Value Author(s) References See Also Examples
Description
This function precalculates parameters on which depth changes to restirict the region on which the depht statistic has to be evaluated on as described in Kustosz and Mueller(2014).
Usage
1 | lin1_theta(dat)
|
Arguments
dat |
Data from an AR(1) Model without intercept |
Value
t1 |
Candidate values for theta1 |
t2 |
Candidate values for theta2 |
Author(s)
Kustosz, Christoph
References
Kustosz, C. (2016). Depth based estimators and tests for
autoregressive processes with application. Ph. D. thesis. TU Dortmund.
Kustosz C., Mueller Ch. H. and Wendler M. (2016). Simplified Simplicial Depth for Regression and
Autoregressive Growth Processes. Journal of Statistical Planning and Inference. In press.
Kustosz C. and Mueller Ch. H. (2014). Analysis of crack growth with robust distribution-
free estimators and tests for nonstationary autoregressive processes. Statistical
Papers 55, 125-140.
See Also
dS_lin2,dS1_lin2,dS2_lin2,dS3_lin2, lin2_CI,est_lin2,est_nlin1
Examples
1 2 3 | y <- RandomARMod_lin2(100, 1.001, 0, 15, "0")
thetas <- lin1_theta(y)
summary(thetas$t1)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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