Pith. sign in

REVIEW 3 cited by

The Jackknife Estimation Method

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1606.00497 v1 pith:YNZJXMHL submitted 2016-06-01 stat.ME

classification stat.ME
keywords resamplingestimationjackknifemethodmethodsoutlineparametricstatistical
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

Statistical resampling methods have become feasible for parametric estimation, hypothesis testing, and model validation now that the computer is a ubiquitous tool for statisticians. This essay focuses on the resampling technique for parametric estimation known as the Jackknife procedure. To outline the usefulness of the method and its place in the general class of statistical resampling techniques, I will quickly delineate two similar resampling methods: the bootstrap and the permutation test. I then outline the Jackknife method and show an example of its use.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Robust detection of hot intragroup medium in optically selected, poor galaxy groups by eROSITA

    astro-ph.GA 2024-12 conditional novelty 6.0 of 10

    Stacked eROSITA data reveal faint hot intragroup gas in optically selected poor galaxy groups, with baryon fractions well below the cosmic mean.

  2. Dark siren cross-correlations and the sensitivity of $H_0$ to methodological choices

    astro-ph.CO 2026-05 unverdicted novelty 5.0 of 10

    Methodological choices in dark siren cross-correlations can mitigate biases in H0 inference when selection effects are built into the model and samples of precise events are sufficiently large.

  3. NIKA2 Cosmological Legacy Survey: Blind detection of galaxy clusters in the COSMOS field via the Sunyaev-Zel'dovich effect

    astro-ph.CO 2025-06 conditional novelty 5.0 of 10

    Blind tSZ detection with NIKA2 at 18.5 arcseconds yields 16 cluster candidates in COSMOS, 8 with counterparts, demonstrating access to low-mass, high-redshift clusters.

Pith tools