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tessl
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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-9/

{
  "context": "This criteria evaluates the engineer's ability to use spreg's SUR models with equation-specific spatial error parameters. The focus is on proper use of SURerrorGM or SURerrorML classes with appropriate configuration for allowing spatial parameters to differ across equations.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "SUR model class usage",
      "description": "Uses appropriate SUR spatial error class (SURerrorGM or SURerrorML) from spreg to estimate the system of equations",
      "max_score": 25
    },
    {
      "name": "Dictionary data structure",
      "description": "Correctly structures input data as dictionaries with bigy and bigX parameters, where keys represent equation identifiers and values contain the corresponding dependent and independent variables for each equation",
      "max_score": 20
    },
    {
      "name": "Equation-specific spatial parameters",
      "description": "Configures the SUR model to estimate equation-specific spatial error parameters (lambda values that differ across equations), using the appropriate model initialization or parameter settings that enable this capability",
      "max_score": 30
    },
    {
      "name": "Spatial parameter extraction",
      "description": "Correctly extracts and returns the spatial error parameter (lambda) for each equation from the fitted model object, accessing equation-specific attributes or multi-equation results",
      "max_score": 15
    },
    {
      "name": "Coefficient and standard error extraction",
      "description": "Correctly extracts coefficient estimates and standard errors for each equation from the fitted SUR model object using appropriate attributes (e.g., betas, std_err, or equation-specific accessors)",
      "max_score": 10
    }
  ]
}