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tessl
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Last updated
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pypipkg:pypi/spreg@1.8.x
tile.json

tessl/pypi-spreg

tessl install tessl/pypi-spreg@1.8.0

Spatial econometric regression models for analyzing geographically-related data interactions.

Agent Success

Agent success rate when using this tile

87%

Improvement

Agent success rate improvement when using this tile compared to baseline

0.95x

Baseline

Agent success rate without this tile

92%

rubric.jsonevals/scenario-10/

{
  "context": "This evaluation assesses how well the engineer uses the spreg package to estimate spatial lag models and compute spatial multiplier effects. The focus is on proper usage of GM_Lag or ML_Lag classes for model estimation and spmultiplier() for decomposing effects into direct, indirect, and total components.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Spatial Lag Model",
      "description": "Uses GM_Lag or ML_Lag class from spreg to estimate a spatial lag model with the provided y, X, and W inputs. The model must be properly instantiated with required parameters.",
      "max_score": 30
    },
    {
      "name": "Multiplier Calculation",
      "description": "Uses the spmultiplier() function to compute spatial multipliers from the fitted model. Must extract direct, indirect, and total effects from the multiplier results.",
      "max_score": 25
    },
    {
      "name": "Multiple Methods",
      "description": "Calculates spatial multipliers using at least two different methods by passing different spat_impacts parameter values ('simple', 'full', or 'power') to the model initialization or calling spmultiplier() with different method parameters.",
      "max_score": 20
    },
    {
      "name": "Spatial Parameter Extraction",
      "description": "Correctly extracts the spatial autoregressive parameter (rho) from the fitted GM_Lag or ML_Lag model object (typically accessed as model.rho or from model.betas).",
      "max_score": 10
    },
    {
      "name": "Effect Decomposition",
      "description": "Properly extracts and returns direct, indirect, and total effects for each independent variable from the multiplier results, ensuring all three effect types are included in the output.",
      "max_score": 10
    },
    {
      "name": "Output Structure",
      "description": "Returns results in the specified dictionary format with keys 'direct', 'indirect', 'total', 'methods', and 'rho', containing appropriate data types (arrays/lists for effects, dict for methods, scalar for rho).",
      "max_score": 5
    }
  ]
}