{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:CMJT7OHL4DGBCZCFHMOYLN3YJC","short_pith_number":"pith:CMJT7OHL","schema_version":"1.0","canonical_sha256":"13133fb8ebe0cc1164453b1d85b778489c47de9c5e3b31dc559a8cb0f36d01f6","source":{"kind":"arxiv","id":"1803.01240","version":1},"attestation_state":"computed","paper":{"title":"An extension of Azzalini's method","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Bo\\v{z}idar V. Popovi\\'c, Filippo Domma, Saralees Nadarajah","submitted_at":"2018-03-03T21:07:16Z","abstract_excerpt":"The aim of this paper is to extend Azzalini's method. This extension is done in two stages: consider two dependent and non-identically distributed random variables say $X_1$ and $X_2$; model the dependence between $X_1$ and $X_2$ by a copula. To illustrate the new method, we assume $X_1$ and $X_2$ are exponential random variables. This assumption leads to a new distribution called the Generalized Weighted Exponential Distribution (GWED), a generalization of Gupta and Kundu (2009)'s Weighted Exponential Distribution (WED). Some mathematical properties of the GWED are derived, and its parameters"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1803.01240","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-03-03T21:07:16Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"118c3a4d6dc62257c61a160a7502e66387f98091bf3bc4028cbe37c4416869d4","abstract_canon_sha256":"a43dffaacd93bbe7547a8a448fb77d6f796f092d3f82231a5704d5ef0d75c384"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:22:01.322442Z","signature_b64":"N5nFu177kADKG1Tom7ziTbE1lcud492PGZPnxmfGHMQWkmcJq02UP/itOqqs8v6xHwFS46H1tLRQxLpG8VrkCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"13133fb8ebe0cc1164453b1d85b778489c47de9c5e3b31dc559a8cb0f36d01f6","last_reissued_at":"2026-05-18T00:22:01.321719Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:22:01.321719Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An extension of Azzalini's method","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Bo\\v{z}idar V. Popovi\\'c, Filippo Domma, Saralees Nadarajah","submitted_at":"2018-03-03T21:07:16Z","abstract_excerpt":"The aim of this paper is to extend Azzalini's method. This extension is done in two stages: consider two dependent and non-identically distributed random variables say $X_1$ and $X_2$; model the dependence between $X_1$ and $X_2$ by a copula. To illustrate the new method, we assume $X_1$ and $X_2$ are exponential random variables. This assumption leads to a new distribution called the Generalized Weighted Exponential Distribution (GWED), a generalization of Gupta and Kundu (2009)'s Weighted Exponential Distribution (WED). Some mathematical properties of the GWED are derived, and its parameters"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.01240","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1803.01240","created_at":"2026-05-18T00:22:01.321837+00:00"},{"alias_kind":"arxiv_version","alias_value":"1803.01240v1","created_at":"2026-05-18T00:22:01.321837+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.01240","created_at":"2026-05-18T00:22:01.321837+00:00"},{"alias_kind":"pith_short_12","alias_value":"CMJT7OHL4DGB","created_at":"2026-05-18T12:32:16.446611+00:00"},{"alias_kind":"pith_short_16","alias_value":"CMJT7OHL4DGBCZCF","created_at":"2026-05-18T12:32:16.446611+00:00"},{"alias_kind":"pith_short_8","alias_value":"CMJT7OHL","created_at":"2026-05-18T12:32:16.446611+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC","json":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC.json","graph_json":"https://pith.science/api/pith-number/CMJT7OHL4DGBCZCFHMOYLN3YJC/graph.json","events_json":"https://pith.science/api/pith-number/CMJT7OHL4DGBCZCFHMOYLN3YJC/events.json","paper":"https://pith.science/paper/CMJT7OHL"},"agent_actions":{"view_html":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC","download_json":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC.json","view_paper":"https://pith.science/paper/CMJT7OHL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1803.01240&json=true","fetch_graph":"https://pith.science/api/pith-number/CMJT7OHL4DGBCZCFHMOYLN3YJC/graph.json","fetch_events":"https://pith.science/api/pith-number/CMJT7OHL4DGBCZCFHMOYLN3YJC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC/action/storage_attestation","attest_author":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC/action/author_attestation","sign_citation":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC/action/citation_signature","submit_replication":"https://pith.science/pith/CMJT7OHL4DGBCZCFHMOYLN3YJC/action/replication_record"}},"created_at":"2026-05-18T00:22:01.321837+00:00","updated_at":"2026-05-18T00:22:01.321837+00:00"}