Bayesianism
0.1 Introduction
Instance of:
AKA:
Distinct from:
English:
Formalization:
The posterior, \(P(H|E)\), is our final credibility over possible states of the world given the evidence we’ve observed. Our prior, \(P(H)\), is the starting credibility we assigned to those states. The marginal, \(P(E)\), is the probability of observing the evidence on average across all the possible states. The likelihood, P(E|H), is the probability of observing that evidence given a particular state of the world is true.
\[ P(H|E) = P(H) \times \frac{P(E|H)}{P(E)} \]
Cites: Wikipedia ; Wikidata ; Wolfram
Code
library(DBI)
# Create an ephemeral in-memory RSQLite database
#con <- dbConnect(RSQLite::SQLite(), dbname = ":memory:")
#dbListTables(con)
#dbWriteTable(con, "mtcars", mtcars)
#dbListTables(con)
#Configuration failed because libpq was not found. Try installing:
#* deb: libpq-dev libssl-dev (Debian, Ubuntu, etc)
#install.packages('RPostgres')
#remotes::install_github("r-dbi/RPostgres")
#Took forever because my file permissions were broken
#pg_lsclusters
require(RPostgres)
Loading required package: RPostgres
0.2 Bayesian
English: Formalization:
\[ \]
Cites:
Code