| cutoff.asymptotic {L2DensityGoFtest} | R Documentation |
Asymptoticaly normal critical value for the goodness-of-fit test statistic \hat{S}_n(h) of Bagkavos, Patil and Wood (2021)
Description
Implements an asymptoticaly normal critical value for testing the goodness-of-fit of a parametrically estimated density with the test statistic S.n.
Usage
cutoff.asymptotic(dist, p1, p2, sig.lev)
Arguments
dist |
The null distribution. |
p1 |
Parameter 1 (vector or object) for the null distribution. |
p2 |
Parameter 2 (vector or object) for the null distribution. |
sig.lev |
Significance level of the hypothesis test. |
Details
Implements the asymptotic critical value defined in Remark 1, Bagkavos, Patil and Wood (2021), equal to z_\alpha \sigma_{0, \theta_0} where z_\alpha is the 1-\alpha quantile of the normal distribution and
\sigma_{0, \theta_0}^2 = 2 \left (\int K^2(u)\,du \right ) \left (\int f^2_0(x; \theta_0)\,dx \right ).
Value
A scalar, the estimate of the asymptotic critical value at the given significance level.
Author(s)
Dimitrios Bagkavos
R implementation and documentation: Dimitrios Bagkavos <dimitrios.bagkavos@gmail.com>
References
Bagkavos, Patil and Wood: Nonparametric goodness-of-fit testing for a continuous multivariate parametric model, (2021), under review.
See Also
cutoff.edgeworth, cutoff.bootstrap