dS2_lin1_test: Test based on dS1 for explosive AR(1) processes without...

In ChrisKust/rexpar: Simplicial Depth for Explosive Autoregressive Processes

Description

The function evaluates the asymptotic test based on d_S^2 proposed in Kustosz, Mueller and Wendler (2016). It returns the test statistic and the decision. The main model is given by

Y_n = θ_1 Y_{n-1} + E_n

with med(E_n)=0.

Usage

  dS2_lin1_test(thetaN, alpha, y, exact)

Arguments

thetaN	Parameter defining the Null hypothesis H0: θ = θ^0. Thereby θ^0 = θ_1^0) as defined by the model.
alpha	Value in (0,1) defining the level of the test.
y	Observed series y=(y_0,...,y_N) for which the parameter test has to be executed.
exact	Switch to decide, weather the exact distribution exact=TRUE or the approximate normal distribution exact=FALSE should be used for the calculation of critical values.

Details

The theoretical details can be found in Kustosz, Mueller and Wendler (2016) and Kustosz and Mueller (2014). The computational details are in Kustosz (2016).

Value

TS	Returns the value of the rescaled and centred test statistic.
phi	Retuns the test decision, phi = 1 means reject H0, and phi = 0 means do not reject H0.

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

dS1_lin2

Examples

  y <- RandomARMod_lin2(1000, 0, 1.01, 15, "0")
  dS2_lin1_test(1.01, 0.05, y)
  dS2_lin1_test(1.1, 0.05, y)

ChrisKust/rexpar documentation built on May 6, 2019, 11:48 a.m.