Cargando…
Finite-Sample Two-Group Composite Hypothesis Testing via Machine Learning
In the problem of composite hypothesis testing, identifying the potential uniformly most powerful (UMP) unbiased test is of great interest. Beyond typical hypothesis settings with exponential family, it is usually challenging to prove the existence and further construct such UMP unbiased tests with...
Autores principales: | Zhan, Tianyu, Kang, Jian |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733814/ https://www.ncbi.nlm.nih.gov/pubmed/36506350 http://dx.doi.org/10.1080/10618600.2021.2020128 |
Ejemplares similares
-
Statistical Hypothesis Testing versus Machine Learning Binary Classification: Distinctions and Guidelines
por: Li, Jingyi Jessica, et al.
Publicado: (2020) -
Analysing Microbial Community Composition through Amplicon Sequencing: From Sampling to Hypothesis Testing
por: Hugerth, Luisa W., et al.
Publicado: (2017) -
Reverse hypothesis machine learning: a practitioner's perspective
por: Kulkarni, Parag
Publicado: (2017) -
Long-term resource variation and group size: A large-sample field test of the Resource Dispersion Hypothesis
por: Johnson, Dominic DP, et al.
Publicado: (2001) -
Testing the reinforcement learning hypothesis of social conformity
por: Levorsen, Marie, et al.
Publicado: (2020)