{"id":"W3206884173","doi":"10.1007/s40300-021-00223-8","title":"A Bayesian piecewise linear model for the detection of breakpoints in housing prices","year":2021,"lang":"en","type":"article","venue":"METRON","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Econometrics; Gibbs sampling; Piecewise linear function; Bayesian probability; Linear regression; Segmented regression; Bayesian inference; Inference; Threshold model; Linear model; Generalized linear model; Sampling (signal processing); Piecewise; Variable (mathematics); Bayesian linear regression; Mathematics; Computer science; Statistics; Artificial intelligence; Bayesian multivariate linear regression","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":[0.002439526,0.0006645629,0.00157868,0.001185201,0.0004962937,0.001380866,0.003189462,0.002279672,0.004995878],"category_scores_gemma":[0.01276558,0.001267791,0.001053577,0.001312876,0.0009326542,0.002580799,0.001243401,0.002267771,0.0008059292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001128663,"about_ca_system_score_gemma":0.0007457415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01563248,"about_ca_topic_score_gemma":0.01132785,"domain_scores_codex":[0.9992909,0.0003161283,0.0000251316,0.0001851061,0.00008577518,0.00009685818],"domain_scores_gemma":[0.9954555,0.003559957,0.0004332807,0.0001739574,0.0002482948,0.0001290268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002640971,0.00005256719,0.003579799,0.00006750115,0.0000810054,0.0001158114,0.0001029669,0.9372092,0.0006953102,0.03013192,0.00130564,0.02639411],"study_design_scores_gemma":[0.00000734588,0.00001094814,0.0003389044,0.000004750965,0.000008030204,0.00001439207,0.000004926634,0.9942121,0.00006677433,0.005197668,0.0001278861,0.000006262787],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07111163,0.0006613606,0.9251744,0.0007178505,0.00004170572,0.00003031347,0.0005801664,0.0004205967,0.001262026],"genre_scores_gemma":[0.9054111,0.0006247383,0.0839517,0.0001637283,0.00008597606,0.0001210287,0.0008691273,0.0001438593,0.008628743],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01563248,"threshold_uncertainty_score":0.03108299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04869576513195278,"score_gpt":0.2512556207142922,"score_spread":0.2025598555823395,"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."}}