UC R Markdown Template

In Rbearcat: University of Cincinnati Themes and Utilities for Econometrics and Data Science

options(kableExtra.latex.load_packages = FALSE)

# load packages
library(Rbearcat)
library(tidyverse)
library(lubridate)
library(haven)
library(stringr)
library(here)
library(knitr)
library(janitor)
library(scales)
library(viridis)
library(RColorBrewer)
library(kableExtra)
library(flextable)
# include additional packages here (if needed)
# library(DT)
# library(ggrepel)

# set default Rmd options
Rbearcat::bcat_setup_rmd()

# set default UC geoms
Rbearcat::set_UC_geoms()

# output type
doc_type <- knitr::opts_knit$get('rmarkdown.pandoc.to')

# if(!knitr::is_latex_output()){
#   
#   knitr::include_graphics(here::here("logo.png"))
#   
# }

First Level Header

Some italized text. Some bold text.

A list:

• item 1
• item 2
• sub-item 1
• sub-item 2.2

A numbered list.

1. item 1
2. item 2
3. item 3

Figures generated by R:

# using function from Rbearcat package
Rbearcat::bcat_plt_line(df = economics,
                     x = date,
                     y = unemploy)

# using ggplot2, but adding custom theme from Rbearcat package
iris %>%
  dplyr::group_by(Species) %>%
  dplyr::summarise(sepal_length_mean = mean(Sepal.Length)) %>%
  ggplot2::ggplot(ggplot2::aes(x = Species, y = sepal_length_mean)) +
  ggplot2::geom_col(fill = Rbearcat::palette_UC["UC Red"]) +
  ggplot2::coord_flip() +
  Rbearcat::theme_UC_vgrid()

# using function from Rbearcat package
Rbearcat::bcat_plt_point(iris,
                      x = Sepal.Length,
                      y = Sepal.Width,
                      color = Species,
                      facet = vars(Species),
                      smooth = TRUE)

A nicely formatted table:

Rbearcat::bcat_fmt_style_table(iris[1:10,])

Inline dynamic text

setosa_mean_length <-
  iris %>%
  dplyr::group_by(Species) %>%
  dplyr::summarise(sepal_length_mean = mean(Sepal.Length)) %>% 
  dplyr::filter(Species == "setosa") %>% 
  dplyr::pull()

The mean sepal length for the setosa species is r setosa_mean_length.

Some math

A vector of observations $y$ having $n$ components is assumed to be a realization of a random variable $Y$ whose components are independently distributed with means $\mu$.

In the original formulation of GLMs, the assumed distribution of $Y$ is a member of an exponential family which have a probability density function of form:

$$f(y_i) = exp{\frac{y_i\theta_i - b(\theta_i)}{a_i(\phi)} + c(y_i, \phi)}$$

where $\theta_i$ and $\phi$ are parameters and $a(\cdot)$, $b(\cdot)$, and $c(\cdot)$ are known functions.

Technical Notes

This document was written in R Markdown, using the rmarkdown [@xie-markdown] and knitr [@xie-knitr] packages.

References

Rbearcat documentation built on March 21, 2026, 5:07 p.m.