Constraining dark energy models using Jackknife and Bootstrap resampling

Fuente: arXiv
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Autori principali: K, Roshna, Fernandes, Nikhil, Praveen, P, Sreenath, V.
Natura: Preprint
Pubblicazione: 2026
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author K, Roshna
Fernandes, Nikhil
Praveen, P
Sreenath, V.
author_facet K, Roshna
Fernandes, Nikhil
Praveen, P
Sreenath, V.
contents Analyses of type Ia supernovae have helped us shed light on the existence and nature of dark energy. Most of these analyses have relied on Bayesian techniques. In this work, we rely on resampling techniques to analyse supernova data. In particular, we use the generalised least squares method together with Jackknife and Bootstrap techniques to estimate parameters of $Λ$CDM, flat $Λ$CDM, $w$CDM, flat $w$CDM, and flat $w_0\,w_a$CDM models from the recent PantheonPlus and SH0ES data. For completeness, we also perform Bayesian analysis using Markov chain Monte Carlo (MCMC) and nested sampling algorithms, and compare the results. We note that resampling techniques can help highlight the limitations of the data. For instance, we see that the Jackknife method estimates a strong positive correlation between $h$ and $M$ and higher standard deviations for both. This may have significant implications for the Hubble tension. We conclude with a discussion of our results.
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institution arXiv
publishDate 2026
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spellingShingle Constraining dark energy models using Jackknife and Bootstrap resampling
K, Roshna
Fernandes, Nikhil
Praveen, P
Sreenath, V.
Cosmology and Nongalactic Astrophysics
Analyses of type Ia supernovae have helped us shed light on the existence and nature of dark energy. Most of these analyses have relied on Bayesian techniques. In this work, we rely on resampling techniques to analyse supernova data. In particular, we use the generalised least squares method together with Jackknife and Bootstrap techniques to estimate parameters of $Λ$CDM, flat $Λ$CDM, $w$CDM, flat $w$CDM, and flat $w_0\,w_a$CDM models from the recent PantheonPlus and SH0ES data. For completeness, we also perform Bayesian analysis using Markov chain Monte Carlo (MCMC) and nested sampling algorithms, and compare the results. We note that resampling techniques can help highlight the limitations of the data. For instance, we see that the Jackknife method estimates a strong positive correlation between $h$ and $M$ and higher standard deviations for both. This may have significant implications for the Hubble tension. We conclude with a discussion of our results.
title Constraining dark energy models using Jackknife and Bootstrap resampling
topic Cosmology and Nongalactic Astrophysics
url https://arxiv.org/abs/2601.16197