{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:X2XUPQQHDYEBMVIMMBBCCD6HWX","short_pith_number":"pith:X2XUPQQH","canonical_record":{"source":{"id":"2207.08384","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2022-07-18T05:23:38Z","cross_cats_sorted":[],"title_canon_sha256":"78c8ee2fa1b673eb74dae5e2bf82611e78b0063d3eba65258ca364526deac311","abstract_canon_sha256":"fc854887f77ae296eb4122a9b860d781d6b901698eaa65b22b84cb0f2a7304f9"},"schema_version":"1.0"},"canonical_sha256":"beaf47c2071e0816550c6042210fc7b5c7448c1a942645cbeb4355b1420b98f1","source":{"kind":"arxiv","id":"2207.08384","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.08384","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"arxiv_version","alias_value":"2207.08384v3","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.08384","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"pith_short_12","alias_value":"X2XUPQQHDYEB","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"pith_short_16","alias_value":"X2XUPQQHDYEBMVIM","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"pith_short_8","alias_value":"X2XUPQQH","created_at":"2026-07-05T11:29:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:X2XUPQQHDYEBMVIMMBBCCD6HWX","target":"record","payload":{"canonical_record":{"source":{"id":"2207.08384","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2022-07-18T05:23:38Z","cross_cats_sorted":[],"title_canon_sha256":"78c8ee2fa1b673eb74dae5e2bf82611e78b0063d3eba65258ca364526deac311","abstract_canon_sha256":"fc854887f77ae296eb4122a9b860d781d6b901698eaa65b22b84cb0f2a7304f9"},"schema_version":"1.0"},"canonical_sha256":"beaf47c2071e0816550c6042210fc7b5c7448c1a942645cbeb4355b1420b98f1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:29:44.433486Z","signature_b64":"v6LOOx3taM/BzeYelxFcEsipqHfcXzVqiPkiBrRNbLQ16aO7YvqhRBDsyNZ+IFJvi7M/H8YrfpNziDehs28eBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"beaf47c2071e0816550c6042210fc7b5c7448c1a942645cbeb4355b1420b98f1","last_reissued_at":"2026-07-05T11:29:44.433028Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:29:44.433028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.08384","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:29:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OYtxrDrFA+GUyRi/O1Im4lOaVi75GW4ZC6hS2P+Immx7uF2o0Dt1Yh4mvc4TYPKV2y9kTFC0NBO7ffaZkA2EBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T08:44:13.807969Z"},"content_sha256":"20fa7cdde076c56768044d20c5b2c45588c4fae9ff59ede392a15a65aff94cd1","schema_version":"1.0","event_id":"sha256:20fa7cdde076c56768044d20c5b2c45588c4fae9ff59ede392a15a65aff94cd1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:X2XUPQQHDYEBMVIMMBBCCD6HWX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Spatio-temporal smoothing, interpolation and prediction of income distributions based on grouped data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Genya Kobayashi, Shonosuke Sugasawa, Yuki Kawakubo","submitted_at":"2022-07-18T05:23:38Z","abstract_excerpt":"The Housing and Land Survey (HLS) of Japan provides municipality-level grouped data on household incomes. Although these data can be used for effective local policymaking, their analyses are hindered by several challenges, such as limited information attributed to grouping, the presence of non-sampled areas, and the very low frequency of implementing surveys. To address these challenges, we propose a novel grouped-data-based spatio-temporal finite mixture model for estimating the income distributions of multiple spatial units at multiple time points. A unique feature of the proposed method is "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.08384","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.08384/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:29:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mI/DbXwX8TZVWTetp8iyiscuqZl2iJnmeRWZaZG26qqyUj6bW9xZ8F+gAVuGvufBgUdnPgZRTQRYJ34Q8+jbCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T08:44:13.808343Z"},"content_sha256":"6538ed59b35794e8d5638bee1d3e9244ccab8c1431eb60d3ce583504ed3c8882","schema_version":"1.0","event_id":"sha256:6538ed59b35794e8d5638bee1d3e9244ccab8c1431eb60d3ce583504ed3c8882"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X2XUPQQHDYEBMVIMMBBCCD6HWX/bundle.json","state_url":"https://pith.science/pith/X2XUPQQHDYEBMVIMMBBCCD6HWX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X2XUPQQHDYEBMVIMMBBCCD6HWX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T08:44:13Z","links":{"resolver":"https://pith.science/pith/X2XUPQQHDYEBMVIMMBBCCD6HWX","bundle":"https://pith.science/pith/X2XUPQQHDYEBMVIMMBBCCD6HWX/bundle.json","state":"https://pith.science/pith/X2XUPQQHDYEBMVIMMBBCCD6HWX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X2XUPQQHDYEBMVIMMBBCCD6HWX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:X2XUPQQHDYEBMVIMMBBCCD6HWX","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"fc854887f77ae296eb4122a9b860d781d6b901698eaa65b22b84cb0f2a7304f9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2022-07-18T05:23:38Z","title_canon_sha256":"78c8ee2fa1b673eb74dae5e2bf82611e78b0063d3eba65258ca364526deac311"},"schema_version":"1.0","source":{"id":"2207.08384","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.08384","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"arxiv_version","alias_value":"2207.08384v3","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.08384","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"pith_short_12","alias_value":"X2XUPQQHDYEB","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"pith_short_16","alias_value":"X2XUPQQHDYEBMVIM","created_at":"2026-07-05T11:29:44Z"},{"alias_kind":"pith_short_8","alias_value":"X2XUPQQH","created_at":"2026-07-05T11:29:44Z"}],"graph_snapshots":[{"event_id":"sha256:6538ed59b35794e8d5638bee1d3e9244ccab8c1431eb60d3ce583504ed3c8882","target":"graph","created_at":"2026-07-05T11:29:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2207.08384/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Housing and Land Survey (HLS) of Japan provides municipality-level grouped data on household incomes. Although these data can be used for effective local policymaking, their analyses are hindered by several challenges, such as limited information attributed to grouping, the presence of non-sampled areas, and the very low frequency of implementing surveys. To address these challenges, we propose a novel grouped-data-based spatio-temporal finite mixture model for estimating the income distributions of multiple spatial units at multiple time points. A unique feature of the proposed method is ","authors_text":"Genya Kobayashi, Shonosuke Sugasawa, Yuki Kawakubo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2022-07-18T05:23:38Z","title":"Spatio-temporal smoothing, interpolation and prediction of income distributions based on grouped data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.08384","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:20fa7cdde076c56768044d20c5b2c45588c4fae9ff59ede392a15a65aff94cd1","target":"record","created_at":"2026-07-05T11:29:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"fc854887f77ae296eb4122a9b860d781d6b901698eaa65b22b84cb0f2a7304f9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2022-07-18T05:23:38Z","title_canon_sha256":"78c8ee2fa1b673eb74dae5e2bf82611e78b0063d3eba65258ca364526deac311"},"schema_version":"1.0","source":{"id":"2207.08384","kind":"arxiv","version":3}},"canonical_sha256":"beaf47c2071e0816550c6042210fc7b5c7448c1a942645cbeb4355b1420b98f1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"beaf47c2071e0816550c6042210fc7b5c7448c1a942645cbeb4355b1420b98f1","first_computed_at":"2026-07-05T11:29:44.433028Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:29:44.433028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"v6LOOx3taM/BzeYelxFcEsipqHfcXzVqiPkiBrRNbLQ16aO7YvqhRBDsyNZ+IFJvi7M/H8YrfpNziDehs28eBA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:29:44.433486Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.08384","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:20fa7cdde076c56768044d20c5b2c45588c4fae9ff59ede392a15a65aff94cd1","sha256:6538ed59b35794e8d5638bee1d3e9244ccab8c1431eb60d3ce583504ed3c8882"],"state_sha256":"ed7f1759024e4a4a68ef8db3b2287fe0f2701776a38bab6928a9c1281ed9c4d4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Gi0pwwpQ26Ks+Gr+jRWwqaedmRChVdC8DnUjjKtNv9DF9m5Pbjn6JNSnnxusb8C/WGjdUP1hti/WlB82qX+FBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T08:44:13.810231Z","bundle_sha256":"1d7b8ac7d1f8e48fae7c0cbbf29d73a9e0fb7134d9f61b7a390099aa359f8535"}}