alcazar90

# python code for reproduce figure 8.3, chapter 8, book: Intro to Probability for Data Science
# https://probability4datascience.com/python08.html
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits import mplot3d
from mpl_toolkits.axes_grid1 import make_axes_locatable

# Bernoulli log-likelihood sequence
N = 50
S = np.linspace(0, N)

alcazar90

library(ISLR)

# prepare data example
df <- ISLR::Hitters[, c("Salary", "Years")]
row.names(df) <- NULL
df$Salary <- log(df$Salary)

# remove the observation with missing values in the response variable
df <- df[!is.na(df$Salary), ]
x <- df$Years