The two-sample problem for Poisson processes: adaptive tests with a nonasymptotic wild bootstrap approach
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Publication:366986
DOI10.1214/13-AOS1114zbMath1273.62102arXiv1203.3572WikidataQ105584284 ScholiaQ105584284MaRDI QIDQ366986
Patricia Reynaud-Bouret, Magalie Fromont, Béatrice Laurent
Publication date: 25 September 2013
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1203.3572
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nonparametric statistical resampling methods (62G09) Monte Carlo methods (65C05) Applications of functional analysis in probability theory and statistics (46N30) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55) Markov processes: hypothesis testing (62M02)
Related Items (11)
Minimax optimality of permutation tests ⋮ Adaptive test of independence based on HSIC measures ⋮ Concentration inequalities, counting processes and adaptive statistics ⋮ On normal approximations for the two-sample problem on multidimensional tori ⋮ The two-sample problem for Poisson processes: adaptive tests with a nonasymptotic wild bootstrap approach ⋮ Bootstrap and permutation tests of independence for point processes ⋮ Unnamed Item ⋮ Chi-squared test for hypothesis testing of homogeneity ⋮ Minimax and adaptive tests for detecting abrupt and possibly transitory changes in a Poisson process ⋮ Exponential inequality for chaos based on sampling without replacement ⋮ A model of Poissonian interactions and detection of dependence
Cites Work
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- The two-sample problem for Poisson processes: adaptive tests with a nonasymptotic wild bootstrap approach
- Sparsity in multiple kernel learning
- Adaptive tests of homogeneity for a Poisson process
- Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality
- Nonparametric hypothesis testing for intensity of the Poisson process
- Linear and convex aggregation of density estimators
- Permutation tests for directional data
- Homogeneity tests for several Poisson populations
- A comparative study of tests for the difference of two Poisson means
- Testing of two sample proportional intensity assumption for non-homogeneous Poisson processes
- On the bootstrap of \(U\) and \(V\) statistics
- Bootstrap, wild bootstrap, and asymptotic normality
- Invariant tests for uniformity on compact Riemannian manifolds based on Sobolev norms
- Bootstrap methods: another look at the jackknife
- Bootstrap and randomization tests of some nonparametric hypotheses
- Exchangeably weighted bootstraps of the general empirical process
- Consistency of the generalized bootstrap for degenerate \(U\)-statistics
- Weighted bootstrapping of \(U\)-statistics
- Asymptotically minimax hypothesis testing for nonparametric alternatives. III
- Random quadratic forms and the bootstrap for \(U\)-statistics
- Adaptive hypothesis testing using wavelets
- Adaptive tests of linear hypotheses by model selection
- How do bootstrap and permutation tests work?
- A more powerful test for comparing two Poisson means
- Adaptive chi-square tests
- Adaptive and spatially adaptive testing of a nonparametric hypothesis.
- Non-asymptotic minimax rates of testing in signal detection
- Estimation and detection of functions from anisotropic Sobolev classes
- Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder)
- Global uniform risk bounds for wavelet deconvolution estimators
- Nonparametric homogeneity tests
- Parametric bootstrap and approximate tests for two Poisson variates
- A Bootstrap Revival of Some Nonparametric Distance Tests
- On comparing two poisson intensity functions
- Experiment Size and Power Comparisons for Two-Sample Poisson Tests
- An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model Against a Nonparametric Alternative
- Rademacher penalties and structural risk minimization
- Tail and moment estimates for some types of chaos
- The Logic of Inductive Inference
- Power Computations for Designing Comparative Poisson Trials
- Testing the hypothesis of proportional hazards in two populations
- Universality, Characteristic Kernels and RKHS Embedding of Measures
- An Introduction to the Theory of Point Processes
- Exact and Approximate Stepdown Methods for Multiple Hypothesis Testing
- The Large-Sample Power of Tests Based on Permutations of Observations
- SOME SIMPLE APPROXIMATE TESTS FOR POISSON VARIATES
- Introduction to nonparametric estimation
- Model selection and error estimation
- Choosing multiple parameters for support vector machines
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