{"paper":{"title":"Goodness-of-fit tests of Gaussianity: constraints on the cumulants of the MAXIMA data","license":"","headline":"","cross_cats":[],"primary_cat":"astro-ph","authors_text":"2), (2)Dpto. de Fisica Moderna. Univ. de Cantabria, 3), (3)Physics Department, (4)Dpto. de Matematicas, A.M. Aliaga (1, CSIC--Univ. de Cantabria, E. Martinez-Gonzalez (1), F. Argueso (4), J.L. Sanz (1), L. Cayon (1, Purdue University, R.B. Barreiro (1) ((1)Instituto de Fisica de Cantabria, Univ. de Oviedo)","submitted_at":"2003-09-22T15:20:52Z","abstract_excerpt":"In this work, goodness-of-fit tests are adapted and applied to CMB maps to detect possible non-Gaussianity. We use Shapiro-Francia test and two Smooth goodness-of-fit tests: one developed by Rayner and Best and another one developed by Thomas and Pierce. The Smooth tests test small and smooth deviations of a prefixed probability function (in our case this is the univariate Gaussian). Also, the Rayner and Best test informs us of the kind of non-Gaussianity we have: excess of skewness, of kurtosis, and so on. These tests are optimal when the data are independent. We simulate and analyse non-Gaus"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"astro-ph/0309586","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}