diff --git a/README.md b/README.md index 7cabd75..c76e0fa 100644 --- a/README.md +++ b/README.md @@ -85,7 +85,7 @@ A 3-by-3 grid varied the NOTEARS L1 penalty and post-estimation threshold. Acros The authorized analysis uses 2,556 complete lots and 37 variables. The pinned NOTEARS candidate has 185 edges; DAGGuard-Exact retains 87 and DAGGuard-Greedy 89. PRRS is adjacent to 60-day nursery mortality in all seven benchmark methods, while MYCO and third-quarter placement are supported by six. Four outgoing NOTEARS mortality relationships are removed by both DAGGuard variants and are absent from all four comparator graphs. -The proprietary row-level data are not distributed. The real-data workflow records a SHA256 hash and exports only non-row-level summaries. Because several production variables are extremely collinear, the application emphasizes recurring relations and variable groups rather than interpreting every individual selected parent as a uniquely identified mechanism. The audit is in `results/swine_application/realdata_collinearity_audit.csv`. +The proprietary row-level data are not distributed. The real-data workflow records a SHA256 hash and exports only non-row-level summaries. ## Repository map @@ -141,7 +141,7 @@ python -m examples.dagguard_quickstart python synthetic_application_twin.py --out results/synthetic_application_twin ``` -The public API tests cover scale invariance for exact refinement, greedy refinement, and pruning pressure; duplicate columns; near-collinearity; near ties; saturated local models; constant responses; and exact or numerically near-exact fits. Additional regression tests check the Gaussian Fisher-z formula, PC-FDR step-up rule, PC-p BY estimator, and the discrete-BIC parameter count used in the Wang adaptation. +The public API tests cover scale invariance for exact refinement, greedy refinement, and pruning pressure; duplicate columns; near ties; saturated local models; constant responses; and exact or numerically near-exact fits. Additional regression tests check the Gaussian Fisher-z formula, PC-FDR step-up rule, PC-p BY estimator, and the discrete-BIC parameter count used in the Wang adaptation. ## Data availability diff --git a/realdata_postselection_diagnostics.py b/realdata_postselection_diagnostics.py index 7b7d32c..4d1f7fe 100644 --- a/realdata_postselection_diagnostics.py +++ b/realdata_postselection_diagnostics.py @@ -110,58 +110,6 @@ def audit_grouping_fields(raw: pd.DataFrame, out: Path) -> None: ]).to_csv(out / "available_grouping_field_audit.csv", index=False) -def collinearity_audit(df: pd.DataFrame, out: Path) -> None: - cont = [v for v in REAL_VARS if v not in BINARY_VARS] - corr = df[cont].corr() - pairs = [] - for i in range(len(cont)): - for j in range(i + 1, len(cont)): - pairs.append((abs(corr.iloc[i, j]), corr.iloc[i, j], cont[i], cont[j])) - pairs.sort(reverse=True) - pd.DataFrame(pairs, columns=["abs_r", "r", "var1", "var2"]).to_csv( - out / "top_correlations.csv", index=False) - - Xs = StandardScaler().fit_transform(df[cont].to_numpy(float)) - singular = np.linalg.svd(Xs, compute_uv=False) - condition = float(singular[0] / singular[-1]) - vifs = [] - for j, name in enumerate(cont): - y = Xs[:, j] - Z = np.delete(Xs, j, axis=1) - beta = np.linalg.lstsq(Z, y, rcond=None)[0] - resid = y - Z @ beta - r2 = 1 - float(resid @ resid) / float(y @ y) - vifs.append((name, r2, 1 / (1 - r2) if r2 < 1 else np.inf)) - vdf = pd.DataFrame(vifs, columns=["variable", "R2_from_other_continuous", "VIF"]) - vdf.sort_values("VIF", ascending=False).to_csv(out / "vif_continuous.csv", index=False) - - def projection_r2(yname, xnames): - y = df[yname].to_numpy(float) - Z = np.column_stack([np.ones(len(df)), df[xnames].to_numpy(float)]) - beta = np.linalg.lstsq(Z, y, rcond=None)[0] - resid = y - Z @ beta - return 1 - float(resid @ resid) / float(((y - y.mean()) ** 2).sum()) - - checks = [ - dict(diagnostic="max_abs_pairwise_correlation", value=pairs[0][0], - detail=f"{pairs[0][2]} vs {pairs[0][3]}; signed r={pairs[0][1]:.6f}"), - dict(diagnostic="standardized_continuous_condition_number", value=condition, - detail="continuous-variable design matrix"), - dict(diagnostic="max_VIF", value=float(vdf.VIF.max()), - detail=str(vdf.sort_values("VIF", ascending=False).iloc[0].variable)), - dict(diagnostic="parity_variable_correlation", - value=float(df["Avg_parity_farrow"].corr(df["avg_parity_at_farrow"])), - detail="Avg_parity_farrow vs avg_parity_at_farrow"), - dict(diagnostic="R2_total_born_from_components", - value=projection_r2("Total_born_avg", ["Born_alive_avg", "Stillborn_avg", "Mummies_avg"]), - detail="Born_alive_avg + Stillborn_avg + Mummies_avg"), - dict(diagnostic="R2_prenatal_losses_from_components", - value=projection_r2("prenatal_losses_avg", ["Stillborn_avg", "Mummies_avg"]), - detail="Stillborn_avg + Mummies_avg"), - ] - pd.DataFrame(checks).to_csv(out / "realdata_collinearity_audit.csv", index=False) - - def write_indegree_distribution(A0: np.ndarray, labels: list[str], out: Path) -> dict: summary = candidate_indegree_summary(A0) indegrees = summary["indegrees"] @@ -352,7 +300,6 @@ def main(): numeric.isna().sum().sort_values(ascending=False).to_csv( args.out / "missingness_by_variable.csv", header=["missing_n"]) audit_grouping_fields(raw, args.out) - collinearity_audit(df, args.out) X = df[REAL_VARS].to_numpy(float) labels = list(REAL_VARS) @@ -473,25 +420,6 @@ def main(): }) pd.DataFrame(ebic_rows).to_csv(args.out / "ebic_greedy_sensitivity.csv", index=False) - remove = ["Avg_parity_farrow", "productive_days_rate", "Total_born_avg", "prenatal_losses_avg"] - keep = [v for v in labels if v not in remove] - ix = [labels.index(v) for v in keep] - Xr = X[:, ix] - A0r = A0[np.ix_(ix, ix)] - exact_r = exact_refine_dag(Xr, A0r) - exact_restricted = exact.adjacency[np.ix_(ix, ix)] - mr = keep.index("mortality_60days") - pd.DataFrame([{ - "analysis": "fixed-candidate redundancy-reduced exact refinement", - "n": Xr.shape[0], "d": Xr.shape[1], "removed_variables": "; ".join(remove), - "restricted_candidate_edges": int(A0r.sum()), - "exact_edges": int(exact_r.adjacency.sum()), - "original_exact_edges_on_retained_variables": int(exact_restricted.sum()), - "jaccard_vs_original_restricted": edge_jaccard(exact_r.adjacency, exact_restricted), - "mortality_in": int(exact_r.adjacency[:, mr].sum()), - "mortality_out": int(exact_r.adjacency[mr, :].sum()), - }]).to_csv(args.out / "redundancy_exact_refinement_sensitivity.csv", index=False) - Xscaled = X.copy() for variable in ["HeadIn", "final_inventory"]: Xscaled[:, labels.index(variable)] /= 1000.0 diff --git a/results/swine_application/rank_diagnostic.csv b/results/swine_application/rank_diagnostic.csv deleted file mode 100644 index 72fe50c..0000000 --- a/results/swine_application/rank_diagnostic.csv +++ /dev/null @@ -1,2 +0,0 @@ -n,d,centered_rank,min_singular_value,max_singular_value,condition_number -2556,37,37,0.3540312323337088,118977.73154080064,336065.63679854263 diff --git a/results/swine_application/realdata_collinearity_audit.csv b/results/swine_application/realdata_collinearity_audit.csv deleted file mode 100644 index adcfe11..0000000 --- a/results/swine_application/realdata_collinearity_audit.csv +++ /dev/null @@ -1,7 +0,0 @@ -diagnostic,value,detail -max_abs_pairwise_correlation,0.9999985734263662,nonproductive_days vs productive_days_rate; signed r=-0.999999 -standardized_continuous_condition_number,1929.247113557193,continuous-variable design matrix -max_VIF,359551.52365682827,productive_days_rate -parity_variable_correlation,0.869450091812237,Avg_parity_farrow vs avg_parity_at_farrow -R2_total_born_from_components,0.9933471395102075,Born_alive_avg + Stillborn_avg + Mummies_avg -R2_prenatal_losses_from_components,0.9693152865431649,Stillborn_avg + Mummies_avg diff --git a/results/swine_application/top_correlations.csv b/results/swine_application/top_correlations.csv deleted file mode 100644 index 28df42a..0000000 --- a/results/swine_application/top_correlations.csv +++ /dev/null @@ -1,466 +0,0 @@ -abs_r,r,var1,var2 -0.9999985734263662,-0.9999985734263662,nonproductive_days,productive_days_rate -0.9753061494890631,0.9753061494890631,mated_inventory_20wks,final_inventory -0.9456888857071207,0.9456888857071207,number_services,final_inventory -0.9224741575802625,0.9224741575802625,mated_inventory_20wks,number_services -0.8694500918122373,0.8694500918122373,Avg_parity_farrow,avg_parity_at_farrow -0.7453092422994336,0.7453092422994336,Total_born_avg,Born_alive_avg -0.7431476067288126,0.7431476067288126,Mummies_avg,prenatal_losses_avg -0.6306737584341003,0.6306737584341003,Stillborn_avg,prenatal_losses_avg -0.6208413687313937,0.6208413687313937,Litters_female_year,PWMFyear -0.6078969127210938,-0.6078969127210938,Mummies_avg,Born_alive_avg -0.5961325901582722,0.5961325901582722,pregnant_105days_rate,Farrowing__rate -0.5311337824270635,-0.5311337824270635,prenatal_losses_avg,Born_alive_avg -0.4730437832778037,0.4730437832778037,productive_days_rate,Farrowing__rate -0.4729917375101991,-0.4729917375101991,nonproductive_days,Farrowing__rate -0.47219015037083295,-0.47219015037083295,repeats__rate,Farrowing__rate -0.46660675661648865,-0.46660675661648865,productive_days_rate,repeats__rate -0.4665927404043444,0.4665927404043444,nonproductive_days,repeats__rate -0.4389722170053802,-0.4389722170053802,PWMFyear,pregnant_105days_rate -0.42008686596311196,-0.42008686596311196,wean_to_service,productive_days_rate -0.4200755011762397,0.4200755011762397,nonproductive_days,wean_to_service -0.41227187763796724,0.41227187763796724,wean_to_service,repeats__rate -0.37715516864002563,-0.37715516864002563,wean_to_service,Last_week_wean_bred_rate -0.3720080461404836,0.3720080461404836,Born_alive_avg,Farrowing__rate -0.3575847856314209,0.3575847856314209,services_per_inventory_N_rate,gilts_bred_rate -0.35692319034107817,-0.35692319034107817,mated_inventory_20wks,gilts_bred_rate -0.34432694383084045,-0.34432694383084045,Mummies_avg,Farrowing__rate -0.3442951531831791,0.3442951531831791,Total_born_avg,Gestation_days -0.34330448959870213,-0.34330448959870213,PWMFyear,Interval_farrows -0.3378852748755306,0.3378852748755306,repeats__rate,Lactation_days -0.3312768236765657,0.3312768236765657,Mummies_avg,repeats__rate -0.3278999932867173,-0.3278999932867173,PWMFyear,Farrowing__rate -0.32509548375979286,-0.32509548375979286,Born_alive_avg,mortality_60days -0.31819238874123296,-0.31819238874123296,productive_days_rate,mortality_60days -0.3181820266287422,0.3181820266287422,nonproductive_days,mortality_60days -0.3136624477165793,0.3136624477165793,nonproductive_days,abortions_rate -0.31364168758794814,-0.31364168758794814,abortions_rate,productive_days_rate -0.3115378391263542,-0.3115378391263542,Litters_female_year,Interval_farrows -0.30570778003602794,-0.30570778003602794,repeats__rate,pregnant_105days_rate -0.3029371450735847,0.3029371450735847,mated_inventory_20wks,HeadIn -0.3014963956649189,-0.3014963956649189,wean_to_service,Farrowing__rate -0.2991155655982585,-0.2991155655982585,Litters_female_year,pregnant_105days_rate -0.29811740363067896,-0.29811740363067896,gilts_bred_rate,final_inventory -0.29511134893001373,0.29511134893001373,Born_alive_avg,productive_days_rate -0.29506170718406693,-0.29506170718406693,nonproductive_days,Born_alive_avg -0.29491741497856966,-0.29491741497856966,Born_alive_avg,repeats__rate -0.29279194914690304,-0.29279194914690304,Litters_female_year,Farrowing__rate -0.2896726758359316,0.2896726758359316,final_inventory,HeadIn -0.28583460569809294,0.28583460569809294,repeats__rate,mortality_60days -0.2836706632431894,0.2836706632431894,abortions_rate,mortality_60days -0.2832454873854902,0.2832454873854902,productive_days_rate,Last_week_wean_bred_rate -0.2831770154182072,-0.2831770154182072,nonproductive_days,Last_week_wean_bred_rate -0.27739600408977794,-0.27739600408977794,Stillborn_avg,Born_alive_avg -0.27207801156919326,0.27207801156919326,Born_alive_avg,Gestation_days -0.26570662835510456,0.26570662835510456,number_services,HeadIn -0.26413044077957826,0.26413044077957826,abortions_rate,Sow_Death_rate -0.2618553752754123,-0.2618553752754123,Mummies_avg,productive_days_rate -0.26183353283787764,0.26183353283787764,nonproductive_days,Mummies_avg -0.259183658617253,0.259183658617253,Total_born_avg,Farrowing__rate -0.25761182631052904,-0.25761182631052904,Farrowing__rate,mortality_60days -0.25653358361755046,0.25653358361755046,prenatal_losses_avg,mortality_60days -0.24592781334318792,0.24592781334318792,Mummies_avg,mortality_60days -0.24492223632426138,-0.24492223632426138,Lactation_days,Farrowing__rate -0.24462764149184965,0.24462764149184965,Total_born_avg,productive_days_rate -0.2445559219044864,-0.2445559219044864,nonproductive_days,Total_born_avg -0.24141028024091957,-0.24141028024091957,nonproductive_days,pregnant_105days_rate -0.24138753263766524,0.24138753263766524,productive_days_rate,pregnant_105days_rate -0.24099425352925233,-0.24099425352925233,number_services,gilts_bred_rate -0.23833683079841445,0.23833683079841445,Born_alive_avg,pregnant_105days_rate -0.23500812492404385,0.23500812492404385,wean_to_service,Mummies_avg -0.23185279637040954,0.23185279637040954,prenatal_losses_avg,repeats__rate -0.22810039421370112,-0.22810039421370112,Mummies_avg,pregnant_105days_rate -0.2249565639483968,0.2249565639483968,Last_week_wean_bred_rate,avg_parity_at_farrow -0.21929617819890232,-0.21929617819890232,prenatal_losses_avg,Farrowing__rate -0.21474234729801306,-0.21474234729801306,wean_to_service,Born_alive_avg -0.21455790759439167,-0.21455790759439167,pregnant_105days_rate,mortality_60days -0.21408602163918036,0.21408602163918036,Mummies_avg,Lactation_days -0.20815125714847077,-0.20815125714847077,abortions_rate,Born_alive_avg -0.2045801343012009,0.2045801343012009,mated_inventory_20wks,Total_born_avg -0.20375240079200294,-0.20375240079200294,Mummies_avg,Last_week_wean_bred_rate -0.20266427133642087,-0.20266427133642087,wean_to_service,pregnant_105days_rate -0.20053087030250885,0.20053087030250885,Total_born_avg,final_inventory -0.193981171746534,0.193981171746534,number_services,Total_born_avg -0.19298278624697657,0.19298278624697657,Last_week_wean_bred_rate,Farrowing__rate -0.19119481346754558,-0.19119481346754558,abortions_rate,Farrowing__rate -0.19003564066466638,0.19003564066466638,Interval_farrows,Lactation_days -0.18849109107870585,-0.18849109107870585,PWSow,repeats__rate -0.18642044171859254,0.18642044171859254,wean_to_service,Lactation_days -0.18321562059434754,0.18321562059434754,Born_alive_avg,PWSow -0.18205281091449088,-0.18205281091449088,productive_days_rate,gilts_bred_rate -0.18203418715496866,0.18203418715496866,nonproductive_days,gilts_bred_rate -0.18118822602507195,0.18118822602507195,Avg_parity_farrow,Stillborn_avg -0.180538688431947,0.180538688431947,number_services,services_per_inventory_N_rate -0.18047314029071107,-0.18047314029071107,pregnant_105days_rate,Lactation_days -0.17888673874861127,-0.17888673874861127,abortions_rate,pregnant_105days_rate -0.17760177446099232,-0.17760177446099232,productive_days_rate,Lactation_days -0.17752870227974527,0.17752870227974527,nonproductive_days,Lactation_days -0.17596489494548848,-0.17596489494548848,gilts_bred_rate,HeadIn -0.17489381600521214,0.17489381600521214,services_per_inventory_N_rate,Last_week_wean_bred_rate -0.1744521668792053,-0.1744521668792053,Total_born_avg,mortality_60days -0.17378495496950438,0.17378495496950438,wean_to_service,mortality_60days -0.1733322986805251,0.1733322986805251,Total_born_avg,Stillborn_avg -0.1730877534975921,0.1730877534975921,Stillborn_avg,avg_parity_at_farrow -0.1725475553925556,0.1725475553925556,mated_inventory_20wks,pregnant_105days_rate -0.17245793191444783,0.17245793191444783,Interval_farrows,repeats__rate -0.17140246018432675,-0.17140246018432675,Stillborn_avg,gilts_bred_rate -0.17005404166483049,0.17005404166483049,Interval_farrows,pregnant_105days_rate -0.16837819615937208,0.16837819615937208,avg_parity_at_farrow,Farrowing__rate -0.1672867305036905,0.1672867305036905,nonproductive_days,Sow_Death_rate -0.16726390837657104,-0.16726390837657104,productive_days_rate,Sow_Death_rate -0.166704407358786,0.166704407358786,Total_born_avg,prenatal_losses_avg -0.1655273422041616,-0.1655273422041616,Mummies_avg,PWSow -0.16489486206575132,0.16489486206575132,mated_inventory_20wks,Stillborn_avg -0.16060387882452545,0.16060387882452545,Total_born_avg,pregnant_105days_rate -0.1601579144052534,0.1601579144052534,wean_to_service,prenatal_losses_avg -0.15999936494241485,-0.15999936494241485,Total_born_avg,gilts_bred_rate -0.15892715768192212,-0.15892715768192212,Total_born_avg,repeats__rate -0.15805633566352492,-0.15805633566352492,prenatal_losses_avg,Last_week_wean_bred_rate -0.1577473131356432,0.1577473131356432,Stillborn_avg,mortality_60days -0.15604689075944472,0.15604689075944472,mated_inventory_20wks,Farrowing__rate -0.15467384838746115,0.15467384838746115,abortions_rate,prenatal_losses_avg -0.15394110495229274,0.15394110495229274,Born_alive_avg,Last_week_wean_bred_rate -0.15315952659234014,0.15315952659234014,Avg_parity_farrow,Last_week_wean_bred_rate -0.15250385609670583,-0.15250385609670583,Lactation_days,final_inventory -0.15120513970601532,-0.15120513970601532,Sow_Death_rate,Farrowing__rate -0.15104142240079377,0.15104142240079377,Sow_Death_rate,Lactation_days -0.15103709404874854,-0.15103709404874854,Born_alive_avg,Lactation_days -0.15024950716873436,0.15024950716873436,pregnant_105days_rate,final_inventory -0.14858683656498972,-0.14858683656498972,mated_inventory_20wks,services_per_inventory_N_rate -0.14683539053806832,0.14683539053806832,Mummies_avg,gilts_bred_rate -0.1464251156759133,0.1464251156759133,Interval_farrows,Last_week_wean_bred_rate -0.14636998938602777,-0.14636998938602777,prenatal_losses_avg,pregnant_105days_rate -0.1460282870112646,-0.1460282870112646,Last_week_wean_bred_rate,Cull_rate_annual -0.14568210138812324,0.14568210138812324,number_services,Stillborn_avg -0.1452743983388562,-0.1452743983388562,nonproductive_days,avg_parity_at_farrow -0.1452474301395062,0.1452474301395062,productive_days_rate,avg_parity_at_farrow -0.1451964184820373,0.1451964184820373,Stillborn_avg,final_inventory -0.1451259748191889,0.1451259748191889,abortions_rate,Mummies_avg -0.14354101117830564,0.14354101117830564,Gestation_days,Interval_farrows -0.14302569854240102,0.14302569854240102,Born_alive_avg,final_inventory -0.14263782410649928,0.14263782410649928,prenatal_losses_avg,Lactation_days -0.14039652691064972,0.14039652691064972,nonproductive_days,services_per_inventory_N_rate -0.14037345859204953,-0.14037345859204953,productive_days_rate,services_per_inventory_N_rate -0.13968359424685267,0.13968359424685267,mated_inventory_20wks,Born_alive_avg -0.13494917779368196,0.13494917779368196,final_inventory,Farrowing__rate -0.13241268820340069,0.13241268820340069,pregnant_105days_rate,avg_parity_at_farrow -0.1312238773432868,0.1312238773432868,abortions_rate,repeats__rate -0.13102660999934135,-0.13102660999934135,repeats__rate,Cull_rate_annual -0.1295653207848796,-0.1295653207848796,wean_to_service,avg_parity_at_farrow -0.12886286429167088,-0.12886286429167088,mated_inventory_20wks,Lactation_days -0.1287535640530212,0.1287535640530212,Avg_parity_farrow,Farrowing__rate -0.1284506172662925,-0.1284506172662925,wean_to_service,PWSow -0.12813054628496845,-0.12813054628496845,abortions_rate,final_inventory -0.12772088111646493,0.12772088111646493,nonproductive_days,prenatal_losses_avg -0.12770186222010668,-0.12770186222010668,prenatal_losses_avg,productive_days_rate -0.12736828564621036,0.12736828564621036,Total_born_avg,PWSow -0.12711339881266046,0.12711339881266046,number_services,pregnant_105days_rate -0.12698734090394184,-0.12698734090394184,repeats__rate,Last_week_wean_bred_rate -0.1262806737204704,0.1262806737204704,number_services,Last_week_wean_bred_rate -0.12594030496124173,0.12594030496124173,number_services,Born_alive_avg -0.12496152146815308,-0.12496152146815308,Born_alive_avg,gilts_bred_rate -0.12446699837276154,-0.12446699837276154,repeats__rate,final_inventory -0.12439663763698253,-0.12439663763698253,abortions_rate,Total_born_avg -0.12292362625840801,-0.12292362625840801,PWMFyear,avg_parity_at_farrow -0.12273921727469198,-0.12273921727469198,Total_born_avg,Mummies_avg -0.12209401084484386,-0.12209401084484386,number_services,abortions_rate -0.1220813537063873,0.1220813537063873,repeats__rate,Sow_Death_rate -0.12208036400104369,0.12208036400104369,number_services,Gestation_days -0.12190325076831537,0.12190325076831537,Stillborn_avg,Sow_Death_rate -0.1213876537856734,0.1213876537856734,productive_days_rate,HeadIn -0.12136187502404111,-0.12136187502404111,nonproductive_days,HeadIn -0.12112439744851428,-0.12112439744851428,wean_to_service,Total_born_avg -0.11974042158623692,-0.11974042158623692,services_per_inventory_N_rate,HeadIn -0.11937536727897156,0.11937536727897156,avg_parity_at_farrow,HeadIn -0.11849805728781868,-0.11849805728781868,services_per_inventory_N_rate,Cull_rate_annual -0.11810889514600474,-0.11810889514600474,Born_alive_avg,Sow_Death_rate -0.11694922887767924,-0.11694922887767924,gilts_bred_rate,Farrowing__rate -0.11661450154801237,-0.11661450154801237,mated_inventory_20wks,abortions_rate -0.11588827240337335,0.11588827240337335,number_services,Farrowing__rate -0.11471618103039877,-0.11471618103039877,number_services,Lactation_days -0.1139181886784975,0.1139181886784975,mated_inventory_20wks,productive_days_rate -0.11388213891090708,-0.11388213891090708,mated_inventory_20wks,nonproductive_days -0.11385437914133249,-0.11385437914133249,services_per_inventory_N_rate,final_inventory -0.11348074168640293,0.11348074168640293,Gestation_days,final_inventory -0.11309598112034583,0.11309598112034583,mated_inventory_20wks,Gestation_days -0.1126566973925259,0.1126566973925259,wean_to_service,Interval_farrows -0.11093832210260626,-0.11093832210260626,Litters_female_year,avg_parity_at_farrow -0.11090227001965872,-0.11090227001965872,mated_inventory_20wks,mortality_60days -0.11000461450057124,0.11000461450057124,Farrowing__rate,HeadIn -0.10993271849372184,0.10993271849372184,Avg_parity_farrow,productive_days_rate -0.10992335152713435,-0.10992335152713435,Avg_parity_farrow,nonproductive_days -0.109818352141171,0.109818352141171,Last_week_wean_bred_rate,pregnant_105days_rate -0.10944287109147903,-0.10944287109147903,pregnant_105days_rate,Sow_Death_rate -0.10901610263290942,-0.10901610263290942,mated_inventory_20wks,repeats__rate -0.10870553204678682,-0.10870553204678682,PWSow,mortality_60days -0.1066651347998609,-0.1066651347998609,final_inventory,mortality_60days -0.10622124749467225,-0.10622124749467225,prenatal_losses_avg,PWSow -0.1061806959645968,0.1061806959645968,Mummies_avg,services_per_inventory_N_rate -0.10584198694033516,0.10584198694033516,Lactation_days,mortality_60days -0.10541607827867368,0.10541607827867368,Gestation_days,avg_parity_at_farrow -0.10274519325445426,-0.10274519325445426,gilts_bred_rate,Sow_Death_rate -0.10249691157787764,0.10249691157787764,productive_days_rate,final_inventory -0.10244806558972053,-0.10244806558972053,nonproductive_days,final_inventory -0.10227693878541075,0.10227693878541075,Sow_Death_rate,mortality_60days -0.10170578533917585,-0.10170578533917585,repeats__rate,HeadIn -0.10120374796540241,-0.10120374796540241,mated_inventory_20wks,Mummies_avg -0.10117630420003101,-0.10117630420003101,wean_to_service,HeadIn -0.10070818586831612,-0.10070818586831612,prenatal_losses_avg,Pre_weaning_mortality -0.10037348901519047,-0.10037348901519047,gilts_bred_rate,Last_week_wean_bred_rate -0.1002903934947292,0.1002903934947292,mated_inventory_20wks,Last_week_wean_bred_rate -0.09805697034392251,-0.09805697034392251,number_services,repeats__rate -0.09803331290852181,-0.09803331290852181,Mummies_avg,final_inventory -0.09753333483904875,0.09753333483904875,services_per_inventory_N_rate,repeats__rate -0.09633493075510394,0.09633493075510394,PWSow,pregnant_105days_rate -0.09575803753693896,-0.09575803753693896,gilts_bred_rate,pregnant_105days_rate -0.09558084784404883,0.09558084784404883,Interval_farrows,avg_parity_at_farrow -0.09523743269533037,-0.09523743269533037,avg_parity_at_farrow,mortality_60days -0.094675972959239,-0.094675972959239,Last_week_wean_bred_rate,mortality_60days -0.0945607872928226,0.0945607872928226,abortions_rate,Stillborn_avg -0.09449690918350431,0.09449690918350431,Gestation_days,PWSow -0.09422267238673337,0.09422267238673337,number_services,PWSow -0.09356990278005578,0.09356990278005578,gilts_bred_rate,mortality_60days -0.09324601292936043,0.09324601292936043,Interval_farrows,mortality_60days -0.09229537395503995,0.09229537395503995,Born_alive_avg,HeadIn -0.09091856818102866,0.09091856818102866,services_per_inventory_N_rate,mortality_60days -0.0878126421090611,-0.0878126421090611,Stillborn_avg,Pre_weaning_mortality -0.08773394903633594,-0.08773394903633594,Avg_parity_farrow,wean_to_service -0.08728088083897874,0.08728088083897874,PWSow,HeadIn -0.08600633215240888,0.08600633215240888,Avg_parity_farrow,pregnant_105days_rate -0.08535337441431014,-0.08535337441431014,HeadIn,mortality_60days -0.08534346118718411,-0.08534346118718411,nonproductive_days,PWSow -0.08533619237454575,0.08533619237454575,PWSow,productive_days_rate -0.08520430966649165,-0.08520430966649165,mated_inventory_20wks,PWMFyear -0.0846882933648567,0.0846882933648567,Avg_parity_farrow,mated_inventory_20wks -0.08459232918966424,-0.08459232918966424,number_services,mortality_60days -0.08353198916243536,-0.08353198916243536,abortions_rate,Last_week_wean_bred_rate -0.08343219101347356,0.08343219101347356,Avg_parity_farrow,HeadIn -0.0816264765041295,-0.0816264765041295,Total_born_avg,Sow_Death_rate -0.08146957354608249,0.08146957354608249,Avg_parity_farrow,PWSow -0.08019476475324076,-0.08019476475324076,services_per_inventory_N_rate,Farrowing__rate -0.07849885947335887,0.07849885947335887,abortions_rate,Lactation_days -0.07819760907231739,0.07819760907231739,number_services,productive_days_rate -0.07814162031279664,-0.07814162031279664,nonproductive_days,number_services -0.07812974091890393,0.07812974091890393,Gestation_days,Lactation_days -0.0774644953236098,-0.0774644953236098,Litters_female_year,mated_inventory_20wks -0.07728578852876095,-0.07728578852876095,Lactation_days,HeadIn -0.07702610020959098,-0.07702610020959098,services_per_inventory_N_rate,pregnant_105days_rate -0.07661389660502499,0.07661389660502499,pregnant_105days_rate,HeadIn -0.07551390378632893,0.07551390378632893,PWSow,Last_week_wean_bred_rate -0.0737554869313938,-0.0737554869313938,Litters_female_year,Last_week_wean_bred_rate -0.0735013213255189,0.0735013213255189,Interval_farrows,Sow_Death_rate -0.07269273910053999,0.07269273910053999,prenatal_losses_avg,Sow_Death_rate -0.07261516360838224,0.07261516360838224,PWSow,avg_parity_at_farrow -0.07259050666659034,0.07259050666659034,Stillborn_avg,Gestation_days -0.07197896719024455,-0.07197896719024455,number_services,Mummies_avg -0.07073793008264491,0.07073793008264491,mated_inventory_20wks,PWSow -0.07056457945292757,-0.07056457945292757,Born_alive_avg,services_per_inventory_N_rate -0.07040173927035595,0.07040173927035595,mated_inventory_20wks,avg_parity_at_farrow -0.07033440316628234,-0.07033440316628234,Pre_weaning_mortality,mortality_60days -0.06952768112685538,0.06952768112685538,wean_to_service,gilts_bred_rate -0.06944117084667074,0.06944117084667074,Last_week_wean_bred_rate,final_inventory -0.0692390759376964,0.0692390759376964,PWSow,final_inventory -0.0691484978123783,-0.0691484978123783,Gestation_days,mortality_60days -0.06869373989714496,0.06869373989714496,Avg_parity_farrow,prenatal_losses_avg -0.06867342435310535,-0.06867342435310535,Avg_parity_farrow,Sow_Death_rate -0.06837843855187697,-0.06837843855187697,prenatal_losses_avg,HeadIn -0.06734434236289881,-0.06734434236289881,repeats__rate,avg_parity_at_farrow -0.06733589461718673,0.06733589461718673,Avg_parity_farrow,Gestation_days -0.06693226703440222,0.06693226703440222,nonproductive_days,Interval_farrows -0.06692789804022803,-0.06692789804022803,Interval_farrows,productive_days_rate -0.06667138795756848,-0.06667138795756848,Last_week_wean_bred_rate,Lactation_days -0.06574817631197297,-0.06574817631197297,Avg_parity_farrow,Mummies_avg -0.06538015388561445,-0.06538015388561445,Total_born_avg,Pre_weaning_mortality -0.06530790826102387,-0.06530790826102387,abortions_rate,Cull_rate_annual -0.06495992246048718,0.06495992246048718,prenatal_losses_avg,avg_parity_at_farrow -0.06461703876542559,-0.06461703876542559,Avg_parity_farrow,repeats__rate -0.06447856694103345,-0.06447856694103345,Total_born_avg,Lactation_days -0.06395171945946156,-0.06395171945946156,Mummies_avg,avg_parity_at_farrow -0.063355944923155,0.063355944923155,number_services,prenatal_losses_avg -0.06305364686939846,0.06305364686939846,abortions_rate,gilts_bred_rate -0.0630217520203249,-0.0630217520203249,Mummies_avg,HeadIn -0.06275858950468868,0.06275858950468868,Interval_farrows,Farrowing__rate -0.06215327569938912,0.06215327569938912,PWSow,Farrowing__rate -0.06196581823670671,0.06196581823670671,Avg_parity_farrow,number_services -0.061647769937335783,-0.061647769937335783,PWSow,gilts_bred_rate -0.06142306661095874,0.06142306661095874,Interval_farrows,gilts_bred_rate -0.05913445838559181,-0.05913445838559181,Avg_parity_farrow,mortality_60days -0.05889807383872502,0.05889807383872502,Last_week_wean_bred_rate,HeadIn -0.05862263578804773,0.05862263578804773,Gestation_days,Cull_rate_annual -0.0583656124455742,0.0583656124455742,Total_born_avg,avg_parity_at_farrow -0.05709328402486846,0.05709328402486846,Total_born_avg,Last_week_wean_bred_rate -0.05699595935805258,-0.05699595935805258,Avg_parity_farrow,PWMFyear -0.056872452548552735,0.056872452548552735,services_per_inventory_N_rate,Lactation_days -0.05635306277054067,0.05635306277054067,mated_inventory_20wks,prenatal_losses_avg -0.05609992928292281,-0.05609992928292281,Avg_parity_farrow,Litters_female_year -0.05477946364325729,0.05477946364325729,prenatal_losses_avg,services_per_inventory_N_rate -0.054507330235364713,-0.054507330235364713,mated_inventory_20wks,wean_to_service -0.054433947765206,0.054433947765206,Avg_parity_farrow,final_inventory -0.054091601118629824,-0.054091601118629824,Pre_weaning_mortality,repeats__rate -0.05392899905002396,0.05392899905002396,Total_born_avg,HeadIn -0.053921473937843876,-0.053921473937843876,Sow_Death_rate,final_inventory -0.0532953965148217,-0.0532953965148217,nonproductive_days,Pre_weaning_mortality -0.05327920701355836,0.05327920701355836,Pre_weaning_mortality,productive_days_rate -0.05297485077632934,-0.05297485077632934,Interval_farrows,HeadIn -0.05237686587601793,0.05237686587601793,wean_to_service,abortions_rate -0.05169936711360501,-0.05169936711360501,PWMFyear,Stillborn_avg -0.05148743671895684,-0.05148743671895684,wean_to_service,Pre_weaning_mortality -0.050050847273558643,0.050050847273558643,Stillborn_avg,productive_days_rate -0.05002895970948962,-0.05002895970948962,Sow_Death_rate,avg_parity_at_farrow -0.050014541117651835,-0.050014541117651835,nonproductive_days,Stillborn_avg -0.04949990119956251,0.04949990119956251,Pre_weaning_mortality,Farrowing__rate -0.04944712108509183,-0.04944712108509183,abortions_rate,HeadIn -0.048750076789497165,0.048750076789497165,gilts_bred_rate,Lactation_days -0.04871935884822687,0.04871935884822687,wean_to_service,services_per_inventory_N_rate -0.048014555685527795,-0.048014555685527795,Gestation_days,gilts_bred_rate -0.04746997301385075,-0.04746997301385075,Cull_rate_annual,mortality_60days -0.047382453963587645,-0.047382453963587645,Stillborn_avg,HeadIn -0.04680549058429825,-0.04680549058429825,Interval_farrows,final_inventory -0.04650231804333815,0.04650231804333815,prenatal_losses_avg,final_inventory -0.046434974666175424,-0.046434974666175424,PWMFyear,Sow_Death_rate -0.04569680860017597,0.04569680860017597,PWMFyear,Born_alive_avg -0.045557665930340205,0.045557665930340205,Interval_farrows,services_per_inventory_N_rate -0.04466744627411459,-0.04466744627411459,Mummies_avg,Pre_weaning_mortality -0.0444110669901858,0.0444110669901858,wean_to_service,Gestation_days -0.04439906123551341,-0.04439906123551341,wean_to_service,final_inventory -0.04328649999205509,-0.04328649999205509,Litters_female_year,number_services -0.042907544505937735,0.042907544505937735,Gestation_days,Farrowing__rate -0.04239528200550283,0.04239528200550283,PWSow,services_per_inventory_N_rate -0.04177617968164704,-0.04177617968164704,number_services,wean_to_service -0.04175524539124639,0.04175524539124639,gilts_bred_rate,Cull_rate_annual -0.04093115039626859,-0.04093115039626859,Litters_female_year,Stillborn_avg -0.040733865068250164,0.040733865068250164,Gestation_days,pregnant_105days_rate -0.04059673453090395,-0.04059673453090395,PWMFyear,number_services -0.04047950648376078,-0.04047950648376078,Interval_farrows,Cull_rate_annual -0.040192242645274566,0.040192242645274566,Litters_female_year,Born_alive_avg -0.039786621060469735,-0.039786621060469735,Litters_female_year,final_inventory -0.03948576334959395,0.03948576334959395,Pre_weaning_mortality,HeadIn -0.03924569290817991,0.03924569290817991,Gestation_days,Sow_Death_rate -0.039204830832936646,-0.039204830832936646,Total_born_avg,services_per_inventory_N_rate -0.039203851960122806,-0.039203851960122806,PWMFyear,final_inventory -0.03900366772071587,-0.03900366772071587,PWMFyear,repeats__rate -0.03834840643178826,0.03834840643178826,Pre_weaning_mortality,pregnant_105days_rate -0.038253785088639844,-0.038253785088639844,Litters_female_year,repeats__rate -0.03757802265441513,0.03757802265441513,Avg_parity_farrow,Total_born_avg -0.03751694868586659,0.03751694868586659,Born_alive_avg,Cull_rate_annual -0.03727004639193177,-0.03727004639193177,Gestation_days,repeats__rate -0.03717425876968769,-0.03717425876968769,PWMFyear,prenatal_losses_avg -0.03711779841112386,0.03711779841112386,Litters_female_year,PWSow -0.03671571174093006,0.03671571174093006,avg_parity_at_farrow,Lactation_days -0.03586095356696227,-0.03586095356696227,Mummies_avg,Cull_rate_annual -0.035731985821156824,0.035731985821156824,Gestation_days,services_per_inventory_N_rate -0.035548982481778485,0.035548982481778485,services_per_inventory_N_rate,Sow_Death_rate -0.03552710196427291,0.03552710196427291,Gestation_days,Last_week_wean_bred_rate -0.03528971381044943,-0.03528971381044943,Litters_female_year,prenatal_losses_avg -0.03470261906308092,0.03470261906308092,prenatal_losses_avg,Gestation_days -0.0342690928461112,-0.0342690928461112,number_services,Interval_farrows -0.03395380538917372,-0.03395380538917372,Interval_farrows,Pre_weaning_mortality -0.03384781321301501,0.03384781321301501,PWSow,Cull_rate_annual -0.03378244597740452,-0.03378244597740452,Litters_female_year,Lactation_days -0.03297335251496573,0.03297335251496573,Cull_rate_annual,Farrowing__rate -0.03261430349767875,-0.03261430349767875,nonproductive_days,Gestation_days -0.03256934403888453,0.03256934403888453,Gestation_days,productive_days_rate -0.03189559944823557,-0.03189559944823557,Litters_female_year,HeadIn -0.03184276547558316,0.03184276547558316,PWSow,Lactation_days -0.03152002410010728,-0.03152002410010728,Avg_parity_farrow,abortions_rate -0.030785453189863286,-0.030785453189863286,PWMFyear,Lactation_days -0.029707207581381876,0.029707207581381876,Gestation_days,HeadIn -0.029634130419361693,0.029634130419361693,number_services,avg_parity_at_farrow -0.02873039918318234,-0.02873039918318234,Mummies_avg,Gestation_days -0.02867567092059299,-0.02867567092059299,abortions_rate,PWSow -0.02858831778585478,-0.02858831778585478,PWMFyear,Last_week_wean_bred_rate -0.026514859877961077,-0.026514859877961077,abortions_rate,Pre_weaning_mortality -0.026007344883360824,-0.026007344883360824,prenatal_losses_avg,Cull_rate_annual -0.02573901503507842,0.02573901503507842,PWMFyear,Total_born_avg -0.025301479678311,-0.025301479678311,mated_inventory_20wks,Sow_Death_rate -0.024599164121336104,0.024599164121336104,Total_born_avg,Cull_rate_annual -0.024426659862411243,0.024426659862411243,pregnant_105days_rate,Cull_rate_annual -0.023198978895462213,-0.023198978895462213,Cull_rate_annual,Lactation_days -0.023053213934399762,-0.023053213934399762,abortions_rate,Gestation_days -0.022963461292522015,0.022963461292522015,Last_week_wean_bred_rate,Sow_Death_rate -0.022534323004347205,-0.022534323004347205,PWMFyear,Cull_rate_annual -0.02247374661093888,-0.02247374661093888,number_services,Sow_Death_rate -0.02237435861712538,0.02237435861712538,PWMFyear,PWSow -0.022226280957133925,0.022226280957133925,Cull_rate_annual,avg_parity_at_farrow -0.022136662562152305,-0.022136662562152305,Pre_weaning_mortality,Sow_Death_rate -0.02181220561731336,0.02181220561731336,Cull_rate_annual,HeadIn -0.02162673406636091,0.02162673406636091,Pre_weaning_mortality,Cull_rate_annual -0.02128928071429938,-0.02128928071429938,PWMFyear,productive_days_rate -0.021234157546308908,-0.021234157546308908,number_services,Cull_rate_annual -0.021214218376072486,0.021214218376072486,PWMFyear,nonproductive_days -0.0210512008581733,0.0210512008581733,abortions_rate,Interval_farrows -0.021032853261752575,0.021032853261752575,Avg_parity_farrow,Lactation_days -0.020920653692684206,-0.020920653692684206,Stillborn_avg,Interval_farrows -0.020798826143061264,0.020798826143061264,Gestation_days,Pre_weaning_mortality -0.02063362829813024,0.02063362829813024,abortions_rate,services_per_inventory_N_rate -0.020585659514698,-0.020585659514698,Stillborn_avg,services_per_inventory_N_rate -0.020166401188772474,-0.020166401188772474,Stillborn_avg,Mummies_avg -0.019373672690771122,0.019373672690771122,Litters_female_year,Total_born_avg -0.019097125919132322,-0.019097125919132322,Litters_female_year,abortions_rate -0.019058239629179206,-0.019058239629179206,prenatal_losses_avg,gilts_bred_rate -0.01871815486174236,-0.01871815486174236,wean_to_service,Cull_rate_annual -0.01787809286202111,-0.01787809286202111,Litters_female_year,Mummies_avg -0.01756046468475732,0.01756046468475732,Sow_Death_rate,HeadIn -0.016855179853113706,-0.016855179853113706,Litters_female_year,mortality_60days -0.016283720151503082,-0.016283720151503082,PWMFyear,mortality_60days -0.016238802464313508,0.016238802464313508,mated_inventory_20wks,Cull_rate_annual -0.01591758127072255,0.01591758127072255,Mummies_avg,Sow_Death_rate -0.01582017245877781,-0.01582017245877781,Stillborn_avg,Lactation_days -0.015743207478478866,-0.015743207478478866,Avg_parity_farrow,Born_alive_avg -0.015358307635727545,-0.015358307635727545,PWMFyear,abortions_rate -0.015195561086963807,-0.015195561086963807,Litters_female_year,productive_days_rate -0.015147587219012123,0.015147587219012123,Litters_female_year,nonproductive_days -0.01473786211747801,0.01473786211747801,Pre_weaning_mortality,avg_parity_at_farrow -0.014684522518849464,-0.014684522518849464,repeats__rate,gilts_bred_rate -0.014522423482862664,-0.014522423482862664,PWMFyear,HeadIn -0.0137679029408012,0.0137679029408012,avg_parity_at_farrow,final_inventory -0.013653076762016828,-0.013653076762016828,Litters_female_year,Sow_Death_rate -0.013346560883792234,-0.013346560883792234,Litters_female_year,Cull_rate_annual -0.012851512217761476,-0.012851512217761476,Litters_female_year,services_per_inventory_N_rate -0.01283878873954621,-0.01283878873954621,prenatal_losses_avg,Interval_farrows -0.01223885107584691,-0.01223885107584691,Stillborn_avg,Last_week_wean_bred_rate -0.011317833376409916,0.011317833376409916,PWMFyear,gilts_bred_rate -0.011313293295100047,-0.011313293295100047,PWMFyear,Pre_weaning_mortality -0.011285368204147148,-0.011285368204147148,Pre_weaning_mortality,final_inventory -0.011060227565893902,-0.011060227565893902,PWMFyear,Mummies_avg -0.010820306504681408,-0.010820306504681408,Litters_female_year,Gestation_days -0.010768189742803568,0.010768189742803568,Born_alive_avg,Interval_farrows -0.010709358993311834,0.010709358993311834,Avg_parity_farrow,Interval_farrows -0.010587299144361679,-0.010587299144361679,Litters_female_year,Pre_weaning_mortality -0.010418300417639966,-0.010418300417639966,Pre_weaning_mortality,services_per_inventory_N_rate -0.010074721388296076,0.010074721388296076,Born_alive_avg,Pre_weaning_mortality -0.010062460208843911,-0.010062460208843911,Cull_rate_annual,Sow_Death_rate -0.009994273316036023,0.009994273316036023,Litters_female_year,wean_to_service -0.009800819644413691,0.009800819644413691,wean_to_service,Stillborn_avg -0.00950715199239358,0.00950715199239358,wean_to_service,Sow_Death_rate -0.00948178301723084,0.00948178301723084,gilts_bred_rate,avg_parity_at_farrow -0.009126279401481285,-0.009126279401481285,abortions_rate,avg_parity_at_farrow -0.009125714760368449,0.009125714760368449,Mummies_avg,Interval_farrows -0.009049459239630965,-0.009049459239630965,number_services,Pre_weaning_mortality -0.00863921016964651,0.00863921016964651,Avg_parity_farrow,Pre_weaning_mortality -0.00861852725139977,0.00861852725139977,Stillborn_avg,PWSow -0.008115736683855217,-0.008115736683855217,PWMFyear,Gestation_days -0.008038088034009912,0.008038088034009912,Pre_weaning_mortality,Lactation_days -0.0077654857366857375,-0.0077654857366857375,Avg_parity_farrow,gilts_bred_rate -0.007489306047982554,0.007489306047982554,Stillborn_avg,repeats__rate -0.007312948822698942,-0.007312948822698942,mated_inventory_20wks,Interval_farrows -0.007309031026035723,-0.007309031026035723,PWSow,Sow_Death_rate -0.006752663427002687,-0.006752663427002687,Pre_weaning_mortality,PWSow -0.006688602244299953,0.006688602244299953,Stillborn_avg,pregnant_105days_rate -0.005951960058253506,-0.005951960058253506,Cull_rate_annual,final_inventory -0.005919013163451782,-0.005919013163451782,Avg_parity_farrow,Cull_rate_annual -0.005302305104505264,0.005302305104505264,services_per_inventory_N_rate,avg_parity_at_farrow -0.005197309588703351,0.005197309588703351,Pre_weaning_mortality,gilts_bred_rate -0.004863346119978179,0.004863346119978179,Born_alive_avg,avg_parity_at_farrow -0.004128689099222812,0.004128689099222812,PWMFyear,wean_to_service -0.003914705997008096,0.003914705997008096,Stillborn_avg,Cull_rate_annual -0.003637173912377008,0.003637173912377008,PWMFyear,services_per_inventory_N_rate -0.003447611158556792,0.003447611158556792,productive_days_rate,Cull_rate_annual -0.0033629657995088067,0.0033629657995088067,Pre_weaning_mortality,Last_week_wean_bred_rate -0.003349662683704804,-0.003349662683704804,nonproductive_days,Cull_rate_annual -0.0030599269532399142,-0.0030599269532399142,mated_inventory_20wks,Pre_weaning_mortality -0.0030061329745498374,0.0030061329745498374,Total_born_avg,Interval_farrows -0.0028153085450969765,0.0028153085450969765,Interval_farrows,PWSow -0.0026516864394238535,0.0026516864394238535,Avg_parity_farrow,services_per_inventory_N_rate -0.0008922124538665889,-0.0008922124538665889,Litters_female_year,gilts_bred_rate -0.00020068896515083973,-0.00020068896515083973,Stillborn_avg,Farrowing__rate diff --git a/results/swine_application/vif_continuous.csv b/results/swine_application/vif_continuous.csv deleted file mode 100644 index 0f7bf07..0000000 --- a/results/swine_application/vif_continuous.csv +++ /dev/null @@ -1,32 +0,0 @@ -variable,R2_from_other_continuous,VIF -productive_days_rate,0.9999972187574403,359551.52365682827 -nonproductive_days,0.9999972185238294,359521.3256062593 -Born_alive_avg,0.9979214564283401,481.1061041176046 -Total_born_avg,0.9968458608190381,317.04371387157664 -prenatal_losses_avg,0.9957732315184955,236.5873608587276 -Mummies_avg,0.992629866638827,135.68275511378897 -Stillborn_avg,0.9884509490883273,86.58720163656865 -final_inventory,0.9858796341231824,70.81969466823573 -number_services,0.9847466471688096,65.55935675697309 -mated_inventory_20wks,0.9664149298275823,29.775135048586723 -services_per_inventory_N_rate,0.8778652321357321,8.18767675647716 -avg_parity_at_farrow,0.7996924915031198,4.992324089616317 -Avg_parity_farrow,0.7785308991889114,4.515302569693422 -Farrowing__rate,0.5735103690435314,2.3447228898797516 -PWMFyear,0.507418456576707,2.0301207248860806 -repeats__rate,0.47551145041046694,1.9066193166325636 -pregnant_105days_rate,0.4673674508519633,1.8774669358820315 -gilts_bred_rate,0.4355496684045834,1.771635065167743 -Litters_female_year,0.41873505485342566,1.7203858728274686 -Gestation_days,0.4151485289604837,1.709835829296279 -wean_to_service,0.3508241951378108,1.5404147728707878 -Last_week_wean_bred_rate,0.33733274861113516,1.5090529944012314 -Interval_farrows,0.27089393404339857,1.3715425597069755 -mortality_60days,0.24451001869337707,1.3236442901208247 -abortions_rate,0.22742115076880687,1.2943662656505774 -Lactation_days,0.22078696786237328,1.2833460924757445 -Sow_Death_rate,0.1679704141683691,1.2018803381859062 -HeadIn,0.15068054392920027,1.1774132722995567 -Cull_rate_annual,0.11565492948141254,1.130780317929054 -PWSow,0.10718957427562392,1.120058605037745 -Pre_weaning_mortality,0.03206454699838779,1.0331267409401672 diff --git a/tests/test_dagguard_api.py b/tests/test_dagguard_api.py index 76779eb..c2cc438 100644 --- a/tests/test_dagguard_api.py +++ b/tests/test_dagguard_api.py @@ -42,19 +42,6 @@ def test_duplicate_candidate_parent_is_rejected(self): with self.assertRaisesRegex(ValueError, "rank deficient"): refine_dag(X, candidate, method="exact") - def test_near_collinearity_is_handled_when_full_rank(self): - rng = np.random.default_rng(13) - x0 = rng.normal(size=300) - x1 = x0 + 1e-5 * rng.normal(size=300) - y = 0.5 * x0 + 0.5 * x1 + rng.normal(size=300) - X = np.column_stack([x0, x1, y]) - candidate = np.zeros((3, 3), dtype=int) - candidate[0, 2] = 1 - candidate[1, 2] = 1 - result = refine_dag(X, candidate, method="exact") - self.assertTrue(result.globally_optimal) - self.assertTrue(np.all(result.adjacency <= candidate)) - def test_near_tie_is_deterministic(self): rng = np.random.default_rng(19) n = 350