High Dimensional Inference

Junwei Lu
Additional contact information
Junwei Lu: Harvard University

Chapter Chapter 17 in Big Data Analysis, 2025, pp 125-128 from Springer

Abstract: Abstract We start the part of high-dimensional inference by introducing the problems in statistical inference. Given the statistical model { ℙ θ | θ ∈ Θ } $$\{\mathbb {P}_{\theta}|\theta \in \Theta \}$$ , we observe X 1 , … , X n ∼ iid ℙ θ ∗ $$X_1,\ldots,X_n \stackrel {iid}{\sim} \mathbb {P}_{\theta ^*}$$ where θ ∗ $$\theta ^*$$ is the truth. Here are the major goals to estimation and inference.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-03161-7_17

Ordering information: This item can be ordered from
http://www.springer.com/9783032031617

DOI: 10.1007/978-3-032-03161-7_17

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().