{"id":"W4249156837","doi":"10.1002/9781119214656.ch2","title":"Location and Scale","year":2018,"lang":"en","type":"other","venue":"Wiley series in probability and statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Statistics Canada","funders":"","keywords":"Estimator; Confidence interval; Mathematics; Robustness (evolution); Applied mathematics; Statistic; Location parameter; Statistics; Newton's method; Confidence region; Least absolute deviations; M-estimator; Coverage probability; Normal distribution; Scale (ratio); Nonlinear system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003572282,0.001144423,0.001437201,0.002836179,0.001259069,0.00596026,0.001790354,0.002124586,0.01833731],"category_scores_gemma":[0.03063312,0.0008425399,0.00149046,0.003183285,0.003514466,0.007753541,0.004008406,0.003030389,0.006839284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001306982,"about_ca_system_score_gemma":0.00103103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001757571,"about_ca_topic_score_gemma":0.0009540147,"domain_scores_codex":[0.9965639,0.0007446835,0.0001745924,0.001173993,0.001100777,0.000242072],"domain_scores_gemma":[0.992388,0.003213382,0.001234937,0.001657754,0.001218681,0.0002873303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004156899,0.00001510059,0.003477617,0.0002185485,0.00006096526,0.0001423174,0.0003936662,0.009541338,0.001587163,0.8495843,0.007878386,0.1270591],"study_design_scores_gemma":[0.00001871773,0.00006099379,0.006493638,0.0002422717,0.00006422684,0.001042375,0.0003794803,0.02742802,0.001818686,0.8366908,0.1256609,0.00009981135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009629303,0.006186682,0.9018902,0.002110128,0.0007245822,0.00007754296,0.000668493,0.0006685938,0.07804445],"genre_scores_gemma":[0.5208843,0.01425329,0.3746922,0.002021768,0.003733704,0.0005091414,0.001535342,0.001778842,0.08059147],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01833731,"threshold_uncertainty_score":0.06134439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05491063455273117,"score_gpt":0.3634635667546845,"score_spread":0.3085529322019533,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}