Data-driven tests of uniformity on product manifolds
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Publication:840735
DOI10.1016/j.jspi.2009.05.019zbMath1206.62105OpenAlexW1999063634MaRDI QIDQ840735
Publication date: 14 September 2009
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2009.05.019
Directional data; spatial statistics (62H11) Parametric hypothesis testing (62F03) Hypothesis testing in multivariate analysis (62H15) Asymptotic properties of parametric tests (62F05)
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Cites Work
- Nonparametric estimation of a probability density on a Riemannian manifold using Fourier expansions
- Data-driven Sobolev tests of uniformity on compact Riemannian manifolds
- Exponential models for directional data
- Invariant tests for uniformity on compact Riemannian manifolds based on Sobolev norms
- Estimating the dimension of a model
- Asymptotic optimality of data-driven Neyman's tests for uniformity
- Data driven smooth tests for composite hypotheses
- A multivariate Kolmogorov-Smirnov test of goodness of fit
- Intermediate approach to comparison of some goodness-of-fit tests
- A data driven smooth test for circular uniformity
- Generalized intermediate efficiency of goodness-of-fit tests.
- Consistency and Monte Carlo simulation of a data driven version of smooth goodness-of-fit tests
- Data-Driven Version of Neyman's Smooth Test of Fit
- Data driven smooth tests for composite hypotheses comparison of powers
- Data-Driven Smooth Tests When the Hypothesis Is Composite
- Remarks on a Multivariate Transformation
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