svmiller

############################################################################################
# This R function helps to interpret the output of the urca::ur.df function.
# The rules are based on https://stats.stackexchange.com/questions/24072/interpreting-rs-ur-df-dickey-fuller-unit-root-test-results
#
# urdf is the output of the urca::ur.df function
# level is one of c("1pct", "5pct", "10pct")
#
# Author: Hank Roark
# Date: October 2019
############################################################################################

svmiller

library(tidyverse)
library(stevemisc)

jenny()

num_nums <- tibble()

for (i in 1:100) {
  tibble(x = runif(50),
         runsum = cumsum(x),

svmiller

# I'm teaching myself some shit. Bear with me.

using RData, DataFrame

df = load("/home/steve/Dropbox/projects/stevemisc/data/strategic_rivalries.rda")

df # not what I want...
df2 = DataFrame(df)[:, 1] # what I want...

svmiller

---
output: 
  stevetemplates::article:
    fig_caption: true
    keep_tex: TRUE
#bibliography: master.bib
biblio-style: apsr
title: "A Pandoc Markdown Article Starter and Template"
thanks: "Replication files are available on the author's Github account (http://github.com/svmiller). **Current version**: `r format(Sys.time(), '%B %d, %Y')`; **Corresponding author**: svmille@clemson.edu."
author:

svmiller

create_stateyears(system = 'gw') %>%
  filter(year %in% c(1946:2019)) %>%
  add_ucdp_acd(type=c("intrastate"), only_wars = TRUE) %>%
  add_peace_years() %>%
  add_democracy() %>%
  add_creg_fractionalization() %>%
  add_sdp_gdp() %>%
  add_rugged_terrain() -> Data

Data %>%

svmiller

library(tidyverse)
library(peacesciencer)
library(stevemisc)

# https://stackoverflow.com/questions/10893611/storing-tic-toc-values-in-r
library(tictoc)
tic.clearlog()

for (x in 1:100) {
  # passing x to tic() makes it a label at time of the matching toc() call.

svmiller

set.seed(8675309)

tibble(age = round(runif(25,18,80)),
       e = rnorm(25,0,5),
       approval = round(1.25*age + e)) -> Dat

Dat %>%
  ggplot(.,aes(age, approval)) +
  geom_point()

svmiller

library(tidyverse)
library(stevedata)
library(brms)

# what follows is me being an idiot. Don't be Steve. Don't be an idiot.

?therms

# For anyone with a brain: the better you think of Obama, the worse you think of Trump (and vice-versa).

svmiller

# Let's load the packages and the data. -----
# See this instead: http://svmiller.com/blog/2020/04/summarizing-ordinal-models-with-simulation-multivariate-normal/
library(stevemisc)
library(post8000r)
library(tidyverse)


TV16 %>%
  filter(racef == "White") %>%
  filter(state %in% c("Indiana","Ohio","Pennsylvania","Wisconsin","Michigan")) %>%

svmiller

setwd("~/Dropbox/data/gss/GSS_spss-2018")

library(tidyverse)

# haven::read_sav method -----
# ----------------------------

readsav_times = data.frame()

for(i in 1:10) {