cutoff.asymptotic {L2DensityGoFtest}R Documentation

Asymptoticaly normal critical value for the goodness-of-fit test statistic S^n(h)\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 zασ0,θ0 z_\alpha \sigma_{0, \theta_0} where zαz_\alpha is the 1α1-\alpha quantile of the normal distribution and

σ0,θ02=2(K2(u)du)(f02(x;θ0)dx). \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


[Package L2DensityGoFtest version 0.6.0 Index]