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S1 — Inférence Causale en R

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  1. Préface
  2. Bloc I — Penser en causaliste
    3 Chapitres
  3. Bloc II — Dessiner les hypothèses
    3 Chapitres
  4. Bloc III — Concevoir l'analyse
    4 Chapitres
  5. Bloc IV — Estimer l'effet
    3 Chapitres
  6. Bloc V — Nuancer et éprouver
    4 Chapitres
  7. Bloc VI — Affronter les cas difficiles
    4 Chapitres
  8. Bloc VII — Quand les confondeurs se cachent
    2 Chapitres
  9. Bloc VIII — Épilogue : conclure avec sagesse
    1 Chapitre
  10. Annexe — Le bootstrap

Participants 5

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Marier le machine learning et l’estimation causale, sans biais de régularisation.

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