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Pith Number

pith:5CF2FRIB

pith:2026:5CF2FRIB7XEHHQQBCH4BJQVLJD
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Distribution Shift in Missing Data Imputation: A Risk-Based Perspective and Importance-Weighted Correction under MAR

Katarzyna Reluga, Luke Shannon, Song Liu

Standard imputation fails to minimize full-data error under MAR because observed training data differs in distribution from the target.

arxiv:2602.06713 v2 · 2026-02-06 · stat.ML · cs.LG

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\pithnumber{5CF2FRIB7XEHHQQBCH4BJQVLJD}

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Record completeness

1 Bitcoin timestamp
2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

We propose a novel imputation algorithm designed to learn an imputation model from the observed data while explicitly accounting for this distribution shift. Simulation studies show consistent improvements over otherwise identical uncorrected baselines, with average reductions of 3% in RMSE and 7% in Wasserstein distance.

C2weakest assumption

The missingness mechanism satisfies MAR so that missingness probabilities can be estimated from observed data alone and used to form reliable importance weights without introducing additional bias.

C3one line summary

Standard imputation methods fail to minimize full-data MSE under MAR due to distribution shift; a new importance-weighted algorithm corrects for it and improves RMSE by 3% and Wasserstein distance by 7% in simulations.

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-05-18T02:45:05.373339Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

e88ba2c501fdc873c20111f814c2ab48f262c39038db48000c9e16c1097bdf1e

Aliases

arxiv: 2602.06713 · arxiv_version: 2602.06713v2 · doi: 10.48550/arxiv.2602.06713 · pith_short_12: 5CF2FRIB7XEH · pith_short_16: 5CF2FRIB7XEHHQQB · pith_short_8: 5CF2FRIB
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5CF2FRIB7XEHHQQBCH4BJQVLJD \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: e88ba2c501fdc873c20111f814c2ab48f262c39038db48000c9e16c1097bdf1e
Canonical record JSON
{
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    "abstract_canon_sha256": "154ba1dec97baf864cb26a2c7b78f7007eafd1ae3ba81abd47c4ebadabcf3e3b",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.ML",
    "submitted_at": "2026-02-06T14:02:12Z",
    "title_canon_sha256": "fb588127e8260d5200ea0ca53675ea64cfe3ea06cf46aea5de227913b21a62dd"
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