{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:VE2RLMQYH3HUFFQ7DKRKJIQDRH","short_pith_number":"pith:VE2RLMQY","canonical_record":{"source":{"id":"1607.01999","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.EC","submitted_at":"2016-07-07T13:14:43Z","cross_cats_sorted":[],"title_canon_sha256":"831d9960d053d11ee5cfdf7f3dd2b4a56793511e4da5304beef1ba247872d048","abstract_canon_sha256":"8cbd729c563c46f3c7b2e8643932a536da9f15c9fc2c4daa64c2979bb81a6c8e"},"schema_version":"1.0"},"canonical_sha256":"a93515b2183ecf42961f1aa2a4a20389c36e57b4d57f220ba5dfc6818f454f7c","source":{"kind":"arxiv","id":"1607.01999","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.01999","created_at":"2026-05-18T01:11:22Z"},{"alias_kind":"arxiv_version","alias_value":"1607.01999v1","created_at":"2026-05-18T01:11:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.01999","created_at":"2026-05-18T01:11:22Z"},{"alias_kind":"pith_short_12","alias_value":"VE2RLMQYH3HU","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"VE2RLMQYH3HUFFQ7","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"VE2RLMQY","created_at":"2026-05-18T12:30:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:VE2RLMQYH3HUFFQ7DKRKJIQDRH","target":"record","payload":{"canonical_record":{"source":{"id":"1607.01999","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.EC","submitted_at":"2016-07-07T13:14:43Z","cross_cats_sorted":[],"title_canon_sha256":"831d9960d053d11ee5cfdf7f3dd2b4a56793511e4da5304beef1ba247872d048","abstract_canon_sha256":"8cbd729c563c46f3c7b2e8643932a536da9f15c9fc2c4daa64c2979bb81a6c8e"},"schema_version":"1.0"},"canonical_sha256":"a93515b2183ecf42961f1aa2a4a20389c36e57b4d57f220ba5dfc6818f454f7c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:22.832082Z","signature_b64":"HlJiwmE3YdQmwHmV2Q5nojxjkaOifDCXXvH69FVpp4SGU50gYqYlgStPMwOp3r7IajF/BV0l+8gsxpkgXnfXDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a93515b2183ecf42961f1aa2a4a20389c36e57b4d57f220ba5dfc6818f454f7c","last_reissued_at":"2026-05-18T01:11:22.831622Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:22.831622Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1607.01999","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:11:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ct6xpQvq8EwrdkjaapRto2yrqwGjzLapQXl4qEQUncOl9K/Z5wfJnM0AHSLrd61zVKxgD96HTqPe9uY5aRFFCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T11:03:36.597691Z"},"content_sha256":"df958bab34b200af630da67a0538ba591e41775d2aaa978d8f7163b38c14f00f","schema_version":"1.0","event_id":"sha256:df958bab34b200af630da67a0538ba591e41775d2aaa978d8f7163b38c14f00f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:VE2RLMQYH3HUFFQ7DKRKJIQDRH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Inferring the contiguity matrix for spatial autoregressive analysis with applications to house price prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-fin.EC","authors_text":"Sanjay Chawla, Somwrita Sarkar","submitted_at":"2016-07-07T13:14:43Z","abstract_excerpt":"Inference methods in traditional statistics, machine learning and data mining assume that data is generated from an independent and identically distributed (iid) process. Spatial data exhibits behavior for which the iid assumption must be relaxed. For example, the standard approach in spatial regression is to assume the existence of a contiguity matrix which captures the spatial autoregressive properties of the data. However all spatial methods, till now, have assumed that the contiguity matrix is given apriori or can be estimated by using a spatial similarity function. In this paper we propos"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.01999","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:11:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EkjnfFc7FD6XpyGtPyEFB63yrZxrHF1/dnwCJfpNvl/4tcARYDvEjhyaEMdGd+V6g6tqVAaHhAt5ITz4epWgCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T11:03:36.598036Z"},"content_sha256":"4effbf8b543bcc4416d30939c3138d25441674d97208c8429f8bb5b528160f61","schema_version":"1.0","event_id":"sha256:4effbf8b543bcc4416d30939c3138d25441674d97208c8429f8bb5b528160f61"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VE2RLMQYH3HUFFQ7DKRKJIQDRH/bundle.json","state_url":"https://pith.science/pith/VE2RLMQYH3HUFFQ7DKRKJIQDRH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VE2RLMQYH3HUFFQ7DKRKJIQDRH/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":"2026-06-07T11:03:36Z","links":{"resolver":"https://pith.science/pith/VE2RLMQYH3HUFFQ7DKRKJIQDRH","bundle":"https://pith.science/pith/VE2RLMQYH3HUFFQ7DKRKJIQDRH/bundle.json","state":"https://pith.science/pith/VE2RLMQYH3HUFFQ7DKRKJIQDRH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VE2RLMQYH3HUFFQ7DKRKJIQDRH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:VE2RLMQYH3HUFFQ7DKRKJIQDRH","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":"8cbd729c563c46f3c7b2e8643932a536da9f15c9fc2c4daa64c2979bb81a6c8e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.EC","submitted_at":"2016-07-07T13:14:43Z","title_canon_sha256":"831d9960d053d11ee5cfdf7f3dd2b4a56793511e4da5304beef1ba247872d048"},"schema_version":"1.0","source":{"id":"1607.01999","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.01999","created_at":"2026-05-18T01:11:22Z"},{"alias_kind":"arxiv_version","alias_value":"1607.01999v1","created_at":"2026-05-18T01:11:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.01999","created_at":"2026-05-18T01:11:22Z"},{"alias_kind":"pith_short_12","alias_value":"VE2RLMQYH3HU","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_16","alias_value":"VE2RLMQYH3HUFFQ7","created_at":"2026-05-18T12:30:48Z"},{"alias_kind":"pith_short_8","alias_value":"VE2RLMQY","created_at":"2026-05-18T12:30:48Z"}],"graph_snapshots":[{"event_id":"sha256:4effbf8b543bcc4416d30939c3138d25441674d97208c8429f8bb5b528160f61","target":"graph","created_at":"2026-05-18T01:11:22Z","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"},"paper":{"abstract_excerpt":"Inference methods in traditional statistics, machine learning and data mining assume that data is generated from an independent and identically distributed (iid) process. Spatial data exhibits behavior for which the iid assumption must be relaxed. For example, the standard approach in spatial regression is to assume the existence of a contiguity matrix which captures the spatial autoregressive properties of the data. However all spatial methods, till now, have assumed that the contiguity matrix is given apriori or can be estimated by using a spatial similarity function. In this paper we propos","authors_text":"Sanjay Chawla, Somwrita Sarkar","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.EC","submitted_at":"2016-07-07T13:14:43Z","title":"Inferring the contiguity matrix for spatial autoregressive analysis with applications to house price prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.01999","kind":"arxiv","version":1},"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:df958bab34b200af630da67a0538ba591e41775d2aaa978d8f7163b38c14f00f","target":"record","created_at":"2026-05-18T01:11:22Z","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":"8cbd729c563c46f3c7b2e8643932a536da9f15c9fc2c4daa64c2979bb81a6c8e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.EC","submitted_at":"2016-07-07T13:14:43Z","title_canon_sha256":"831d9960d053d11ee5cfdf7f3dd2b4a56793511e4da5304beef1ba247872d048"},"schema_version":"1.0","source":{"id":"1607.01999","kind":"arxiv","version":1}},"canonical_sha256":"a93515b2183ecf42961f1aa2a4a20389c36e57b4d57f220ba5dfc6818f454f7c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a93515b2183ecf42961f1aa2a4a20389c36e57b4d57f220ba5dfc6818f454f7c","first_computed_at":"2026-05-18T01:11:22.831622Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:11:22.831622Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HlJiwmE3YdQmwHmV2Q5nojxjkaOifDCXXvH69FVpp4SGU50gYqYlgStPMwOp3r7IajF/BV0l+8gsxpkgXnfXDw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:11:22.832082Z","signed_message":"canonical_sha256_bytes"},"source_id":"1607.01999","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:df958bab34b200af630da67a0538ba591e41775d2aaa978d8f7163b38c14f00f","sha256:4effbf8b543bcc4416d30939c3138d25441674d97208c8429f8bb5b528160f61"],"state_sha256":"832296d2b7f0ce933df0b51dfea324fcf58aa76a32b0f126c96342bd6d27047a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nhe//SUPOXEGrypcFAXOGaMJX7Vv+YjlOdYCETTm0jlIrhoVwO0+wSJ/Y/aXf+4e6LKU79y39OttZjbQM7hFDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T11:03:36.599971Z","bundle_sha256":"5fe5a4607209f40628b0783123e4fd40b3e9e3df77c765ea7b82b2172d46f9fa"}}