cutoff.asymptotic: Asymptoticaly normal critical value for the goodness-of-fit...

In L2DensityGoFtest: Density Goodness-of-Fit Test

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_α σ_{0, θ_0} where z_α is the 1-α quantile of the normal distribution and

σ_{0, θ_0}^2 = 2 ≤ft (\int K^2(u)\,du \right ) ≤ft (\int f^2_0(x; θ_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 <[e-mail]>

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

L2DensityGoFtest documentation built on Feb. 16, 2023, 9:24 p.m.