datalorax

# Code from Richard McElreath's book, chapter 6
sppnames <- c( "afarensis","africanus","habilis","boisei",
    "rudolfensis","ergaster","sapiens")
brainvolcc <- c( 438 , 452 , 612, 521, 752, 871, 1350 )
masskg <- c( 37.0 , 35.5 , 34.5 , 41.5 , 55.5 , 61.0 , 53.5 )
d <- data.frame( species=sppnames , brain=brainvolcc , mass=masskg )

## R code 6.2
m6.1 <- lm( brain ~ mass , data=d )

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equation_lm <- function(model) {
  rhs  <- colnames(model.matrix(model))[-1]
  lhs  <- all.vars(formula(model))[1]
  lhs_eq <- paste(lhs, "= ")

  betas <- paste0("\\beta_{", seq_along(rhs), "}(")
	rhs_eq <- paste0(betas, rhs, ")")
 	rhs_eq <- paste("\\alpha +", paste(rhs_eq, collapse = " + "))
 	
 	error <- "+ \\epsilon" 

datalorax

library(RSelenium)
library(rvest)
library(tidyverse)
theme_set(theme_minimal(15) +
            theme(plot.title.position = "plot",
                  plot.caption = element_text(color = "gray40", size = 8)))

url <- "https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html"

rd <- rsDriver(browser = "chrome", chromever = "81.0.4044.69")

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library(tidyverse)

by_species <- iris %>%
  group_by(Species) %>% 
  nest()

specific_models <- tibble(
  Species = unique(iris$Species),
  model = list(function(d) lm(Sepal.Length ~ Petal.Width + Petal.Length, d),
               function(d) lm(Sepal.Length ~ Petal.Width, d),

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library(colorspace)
library(rayshader)
library(tidyverse)

mse <- function(x, y, a, b) {
  pred <- a + b*x
  resid2 <- (y - pred)^2
  1/length(y)*sum(resid2)
}

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library(shiny)
library(shinyWidgets)
library(ggplot2)
library(equatiomatic)
library(gtsummary)
library(gt)

ui <- fluidPage(
  titlePanel("equatiomatic w/Shiny"),
  sidebarLayout(