{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:346SLX2CCS6ZQ5ODKK46DSATX7","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":"77e5a66900c0e5e04bab293907ffa46f5cb62e7c76d9a254d8b357af33169c75","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"econ.EM","submitted_at":"2019-01-16T17:30:27Z","title_canon_sha256":"7b96d29933f305d1fc2fd069e32c073911dc45dceb7a21206514d732464b6e87"},"schema_version":"1.0","source":{"id":"1901.05397","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.05397","created_at":"2026-05-17T23:56:10Z"},{"alias_kind":"arxiv_version","alias_value":"1901.05397v1","created_at":"2026-05-17T23:56:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.05397","created_at":"2026-05-17T23:56:10Z"},{"alias_kind":"pith_short_12","alias_value":"346SLX2CCS6Z","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"346SLX2CCS6ZQ5OD","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"346SLX2C","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:db53b7f16da37f3609b07120b7cb9760984be915c1f78f5b5a7b3b7a496027b4","target":"graph","created_at":"2026-05-17T23:56:10Z","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":"This article introduces lassopack, a suite of programs for regularized regression in Stata. lassopack implements lasso, square-root lasso, elastic net, ridge regression, adaptive lasso and post-estimation OLS. The methods are suitable for the high-dimensional setting where the number of predictors $p$ may be large and possibly greater than the number of observations, $n$. We offer three different approaches for selecting the penalization (`tuning') parameters: information criteria (implemented in lasso2), $K$-fold cross-validation and $h$-step ahead rolling cross-validation for cross-section, ","authors_text":"Achim Ahrens, Christian B. Hansen, Mark E. Schaffer","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"econ.EM","submitted_at":"2019-01-16T17:30:27Z","title":"lassopack: Model selection and prediction with regularized regression in Stata"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.05397","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:d209176df90ff8df2c9fd0b784642cf6a22dab9fe6b21f8c4778eb462038bb37","target":"record","created_at":"2026-05-17T23:56:10Z","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":"77e5a66900c0e5e04bab293907ffa46f5cb62e7c76d9a254d8b357af33169c75","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"econ.EM","submitted_at":"2019-01-16T17:30:27Z","title_canon_sha256":"7b96d29933f305d1fc2fd069e32c073911dc45dceb7a21206514d732464b6e87"},"schema_version":"1.0","source":{"id":"1901.05397","kind":"arxiv","version":1}},"canonical_sha256":"df3d25df4214bd9875c352b9e1c813bfffa91138bcf906e420bfccb1078b68ed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"df3d25df4214bd9875c352b9e1c813bfffa91138bcf906e420bfccb1078b68ed","first_computed_at":"2026-05-17T23:56:10.977983Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:10.977983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r3Tn9rkbz9QUmIIPjhIkEdXNqEwBJR+e+Q4QYIU0sTPZbQCrtrjAaZdwWWUCFHJP//r9Uku78QbGQdHNyW6JAA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:10.978615Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.05397","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d209176df90ff8df2c9fd0b784642cf6a22dab9fe6b21f8c4778eb462038bb37","sha256:db53b7f16da37f3609b07120b7cb9760984be915c1f78f5b5a7b3b7a496027b4"],"state_sha256":"d48da5e330315626591856401479b59ca13ec2bf1d9963c3c4be89e23b5848db"}