Linear estimators for Gaussian random variables in Hilbert spaces
Fuente:
arXiv
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2023
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866912719694725120 |
|---|---|
| author | Tappe, Stefan |
| author_facet | Tappe, Stefan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_11083 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Linear estimators for Gaussian random variables in Hilbert spaces Tappe, Stefan Statistics Theory Functional Analysis Probability 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. |
| title | Linear estimators for Gaussian random variables in Hilbert spaces |
| topic | Statistics Theory Functional Analysis Probability |
| url | https://arxiv.org/abs/2305.11083 |