Linear estimators for Gaussian random variables in Hilbert spaces
We study a statistical model for infinite dimensional Gaussian random variables with unknown parameters. For this model we derive linear estimators for the mean and the variance of the Gaussian distribution. Furthermore, we construct confidence intervals and perform hypothesis testing. A linear regression problem in infinite dimensions and some perspectives to statistical and machine learning are presented as well.
Authors
- Stefan Tappe (ORCID: https://orcid.org/0000-0003-3523-0618)
Institutions
- University of Freiburg (DE)
Publication Details
- Journal
- Theory of Probability and Mathematical Statistics
- Published
- 2025-05-09
- DOI
- https://doi.org/10.1090/tpms/1230
- Primary Topic
- Statistical Methods and Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00