The Maximum Likelihood Estimation (MLE) method

2026-06-13

Setting up R Packages

library(tidyverse)
library(ggformula)
library(mosaic)
library(skimr)
library(GGally)
library(infer)

Plot Fonts and Theme

library(systemfonts)
library(showtext)
## Clean the slate
systemfonts::clear_local_fonts()
systemfonts::clear_registry()
##
showtext_opts(dpi = 96) # set DPI for showtext
sysfonts::font_add(
  family = "Alegreya",
  regular = "../../../../../../../fonts/Alegreya-Regular.ttf",
  bold = "../../../../../../../fonts/Alegreya-Bold.ttf",
  italic = "../../../../../../../fonts/Alegreya-Italic.ttf",
  bolditalic = "../../../../../../../fonts/Alegreya-BoldItalic.ttf"
)

sysfonts::font_add(
  family = "Roboto Condensed",
  regular = "../../../../../../../fonts/RobotoCondensed-Regular.ttf",
  bold = "../../../../../../../fonts/RobotoCondensed-Bold.ttf",
  italic = "../../../../../../../fonts/RobotoCondensed-Italic.ttf",
  bolditalic = "../../../../../../../fonts/RobotoCondensed-BoldItalic.ttf"
)
showtext_auto(enable = TRUE) # enable showtext
##
theme_custom <- function() {
  theme_bw(base_size = 10) +

    # theme(panel.widths = unit(11, "cm"),
    #       panel.heights = unit(6.79, "cm")) + # Golden Ratio

    theme(
      plot.margin = margin_auto(t = 1, r = 2, b = 1, l = 1, unit = "cm"),
      plot.background = element_rect(
        fill = "bisque",
        colour = "black",
        linewidth = 1
      )
    ) +

    theme_sub_axis(
      title = element_text(
        family = "Roboto Condensed",
        size = 10
      ),
      text = element_text(
        family = "Roboto Condensed",
        size = 8
      )
    ) +

    theme_sub_legend(
      text = element_text(
        family = "Roboto Condensed",
        size = 6
      ),
      title = element_text(
        family = "Alegreya",
        size = 8
      )
    ) +

    theme_sub_plot(
      title = element_text(
        family = "Alegreya",
        size = 14, face = "bold"
      ),
      title.position = "plot",
      subtitle = element_text(
        family = "Alegreya",
        size = 10
      ),
      caption = element_text(
        family = "Alegreya",
        size = 6
      ),
      caption.position = "plot"
    )
}

## Use available fonts in ggplot text geoms too!
ggplot2::update_geom_defaults(geom = "text", new = list(
  family = "Roboto Condensed",
  face = "plain",
  size = 3.5,
  color = "#2b2b2b"
))
ggplot2::update_geom_defaults(geom = "label", new = list(
  family = "Roboto Condensed",
  face = "plain",
  size = 3.5,
  color = "#2b2b2b"
))

ggplot2::update_geom_defaults(geom = "marquee", new = list(
  family = "Roboto Condensed",
  face = "plain",
  size = 3.5,
  color = "#2b2b2b"
))
ggplot2::update_geom_defaults(geom = "text_repel", new = list(
  family = "Roboto Condensed",
  face = "plain",
  size = 3.5,
  color = "#2b2b2b"
))
ggplot2::update_geom_defaults(geom = "label_repel", new = list(
  family = "Roboto Condensed",
  face = "plain",
  size = 3.5,
  color = "#2b2b2b"
))

## Set the theme
ggplot2::theme_set(new = theme_custom())

## tinytable options
options("tinytable_tt_digits" = 2)
options("tinytable_format_num_fmt" = "significant_cell")
options(tinytable_html_mathjax = TRUE)


## Set defaults for flextable
flextable::set_flextable_defaults(font.family = "Roboto Condensed")

R Package Citations

Package	Version	Citation
equatiomatic	0.4.8	Anderson, Heiss, and Sumners (2026)
ISLR	1.4	James et al. (2021)

Anderson, Daniel, Andrew Heiss, and Jay Sumners. 2026. equatiomatic: Transform Models into “LaTeX” Equations. https://doi.org/10.32614/CRAN.package.equatiomatic.

James, Gareth, Daniela Witten, Trevor Hastie, and Rob Tibshirani. 2021. ISLR: Data for an Introduction to Statistical Learning with Applications in r. https://doi.org/10.32614/CRAN.package.ISLR.