How to infer “Causal Impact”

Recently Google has kindly made available a new open-source package for estimating causal effects in time series, using R.

Read the release announcement on Google’s Open Source blog. The package easily allows to measure the impact of an event (e.g. a marketing campaign) on a time-series of interest (e.g. online sales) by creating a counterfactual “synthetic control” by means of Bayesian statistics.

(For nerds: the technical explanation of the estimator is in the Research at Google website.)

Annunci

1 thought on “How to infer “Causal Impact””

Rispondi

Inserisci i tuoi dati qui sotto o clicca su un'icona per effettuare l'accesso:

Logo WordPress.com

Stai commentando usando il tuo account WordPress.com. Chiudi sessione / Modifica )

Foto Twitter

Stai commentando usando il tuo account Twitter. Chiudi sessione / Modifica )

Foto di Facebook

Stai commentando usando il tuo account Facebook. Chiudi sessione / Modifica )

Google+ photo

Stai commentando usando il tuo account Google+. Chiudi sessione / Modifica )

Connessione a %s...