maxdrohde

# Load packages
library(tidyverse)
library(gganimate)
library(tidymodels)

set.seed(2021)

# Generate true relationship between x and y as piecewise
piecewise <- function(x) {
  case_when(

maxdrohde

library(furrr)

x <- numeric()

for (i in 1:20) {
  future::plan(multisession, workers = i)
  result <- system.time({
    r <- furrr::future_map(1:100,
                           ~ sum(rnorm(1e7)),
                           .options = furrr_options(seed=TRUE))

maxdrohde

# Display data frame as a nicely formatted and interactive GT table
display <- function(df){
  df |>
    gt::gt() |>
    gt::opt_interactive(use_search = TRUE,
                        use_compact_mode = TRUE,
                        use_text_wrapping = TRUE) |>
    gt::opt_stylize(style = 2) |>
    gt::cols_width(everything() ~ px(250))
}

maxdrohde

library(ggplot2)
library(patchwork) # For composing plots
# See https://patchwork.data-imaginist.com/

library(ggtext)    # For formatting text using markdown syntax
# See https://wilkelab.org/ggtext/

# Make a ggplot histogram from a vector of data
gg_hist <- function(x){
  data.frame(x) |>

maxdrohde

library(MASS)
library(plotrix)
library(tidyverse)
library(gganimate)

####################################
## Example 1 (Data by Group with means and estimated means)
####################################

## Number of groups, observations per group

maxdrohde

gen_dataset <- function(){
  b0 <- 3
  b1 <- 7
  x <- 1:10
  linear_predictor <- b0 + b1*x
  y <- rnorm(n = length(linear_predictor), mean=linear_predictor, sd=8)
  df <- tibble(x,y)
  
  # Fit OLS model
  ols_model <- lm(y ~ x, data=df)

maxdrohde

# Using manim community edition

from manim import *

config.frame_width = 22

text1 = MathTex(r"\begin{bmatrix} 3 & 9 & 5 \\ 9 & 4 & 2 \\ 7 & 3 & 6 \end{bmatrix} \begin{bmatrix} 5 & 7 & 2 & 4 \\ 3 & 6 & 9 & 8 \\ 2 & 7 & 1 & 4 \end{bmatrix}")

text2 = MathTex(r"\begin{bmatrix} 3 & 9 & 5 \\ 9 & 4 & 2 \\ 7 & 3 & 6 \end{bmatrix} \begin{bmatrix} 5 & 7 & 2 & 4 \\ 3 & 6 & 9 & 8 \\ 2 & 7 & 1 & 4 \end{bmatrix}", r"&=", r"\begin{bmatrix} 3 \\ 9 \\ 7 \end{bmatrix} \begin{bmatrix} 5 & 7 & 2 & 4 \end{bmatrix} + \begin{bmatrix} 9 \\ 4 \\ 3 \end{bmatrix} \begin{bmatrix} 3 & 6 & 9 & 8 \end{bmatrix} + \begin{bmatrix} 5 \\ 2 \\ 6 \end{bmatrix} \begin{bmatrix} 2 & 7 & 1 & 4 \end{bmatrix} \\")

maxdrohde

library(tidyverse)
library(gganimate)

set.seed(777)

points <- 2* 1e3

x <- runif(points, min = -1, max=1)
y <- runif(points, min=-1, max=1)
inside <- x^2 + y^2 < 1

maxdrohde

library(tidyverse)

set.seed(1)

df <- tibble(x=rnorm(2000),
             y=rnorm(2000)) %>%
  mutate(flag = x+y > 1.5)

df %>%
  ggplot() +

maxdrohde

library(tidymodels)
library(tidyverse)
library(discrim)
library(gganimate)

# grid size
n <- 100

parabolic_grid <-
  expand.grid(X1 = seq(-5, 5, length = n),