data_def_lrml.R

library(dplyr)
library(ggplot2)

n     <- 200 # number of observations
bias  <- 4
slope <- 3.5
dot   <- `%*%` # defined for personal preference 

x   <- rnorm(n) * 2
x_b <- cbind(x, rep(1, n))
y   <- bias + slope * x + rnorm(n)
df  <- data_frame(x = x,  y = y)

learning_rate <- 0.05
n_iterations  <- 100
theta         <- matrix(c(20, 20))

b0    <- vector("numeric", length = n_iterations)
b1    <- vector("numeric", length = n_iterations)
sse_i <- vector("numeric", length = n_iterations)