Elementy potrzebne do wnioskowania bayesowskiego

Podstawy bayesowskiej analizy danych w R

Rasmus Bååth

Data Scientist

Czym jest model generatywny?

Generatywny model leku na zombie

# Parameters
prop_success <- ???
n_zombies <- ???

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- ???
}

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- runif(1, min = 0, max = 1) < prop_success
}

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- runif(1, min = 0, max = 1) < prop_success}

data

FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE FALSE

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- runif(1, min = 0, max = 1) < prop_success
}
data <- as.numeric(data)

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- runif(1, min = 0, max = 1) < prop_success
}
data <- as.numeric(data)
data

0 0 0 1 0 0 0 0 1 0 1 0 0

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- runif(1, min = 0, max = 1) < prop_success
}
data <- as.numeric(data)
data

0 0 1 0 0 0 0 0 0 0 0 0 0

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- runif(1, min = 0, max = 1) < prop_success
}
data <- as.numeric(data)
data

0 1 0 1 1 0 0 1 0 1 0 0 0

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- runif(1, min = 0, max = 1) < prop_success
}
data <- as.numeric(data)
data

0 0 0 0 0 0 0 1 0 0 0 0 0

Generatywny model leku na zombie

# Parameters
prop_success <- 0.15
n_zombies <- 13
# Simulating data
data <- c()
for(zombie in 1:n_zombies) {
  data[zombie] <- runif(1, min = 0, max = 1) < prop_success
}
data <- as.numeric(data)
data

0 0 0 0 1 0 0 0 0 1 0 1 0

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Podstawy bayesowskiej analizy danych w R