{
   "name": "fbsql",
   "abstract": "Closure-preserving formula-based statistical modeling in SQL",
   "description": "FbSQL is a PostgreSQL extension that proposes a statistical modeling DSL faithful to SQL design principles: set-oriented, declarative, closed over relations (relation in, relation out), order-independent, and consistent with SQL NULL semantics. Models are specified with R formula notation; fbsql.fit_glm() fits a GLM (gaussian or binomial) via PL/R and returns a single relation of term rows with model-level columns and a jsonb metadata column, and fbsql.predict_glm() scores a relation from that model relation alone, without R. glm is the first proof of concept of the design.",
   "version": "0.1.0",
   "maintainer": [
      "Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>"
   ],
   "license": "mit",
   "provides": {
      "fbsql": {
         "abstract": "Formula-based GLM fitting and prediction as relations",
         "file": "sql/fbsql--0.1.0.sql",
         "docfile": "README.md",
         "version": "0.1.0"
      }
   },
   "prereqs": {
      "runtime": {
         "requires": {
            "PostgreSQL": "16.0.0",
            "plr": "8.4.0"
         }
      }
   },
   "resources": {
      "homepage": "https://github.com/dsc-chiba-u/FbSQL",
      "bugtracker": {
         "web": "https://github.com/dsc-chiba-u/FbSQL/issues"
      },
      "repository": {
         "url": "https://github.com/dsc-chiba-u/FbSQL.git",
         "web": "https://github.com/dsc-chiba-u/FbSQL",
         "type": "git"
      }
   },
   "generated_by": "Data Science Core, Chiba University",
   "meta-spec": {
      "version": "1.0.0",
      "url": "https://pgxn.org/meta/spec.txt"
   },
   "tags": [
      "statistics",
      "glm",
      "regression",
      "logistic regression",
      "formula",
      "machine learning",
      "plr",
      "r"
   ]
}