alexpghayes

# pak::pak("gpiras/sphet")

library(fastRG)
#> Loading required package: Matrix
library(sphet)

# simulate from y = alpha + trt * gamma + G trt * delta + lambda G y

set.seed(26)

alexpghayes

library(tidyverse)
library(mgcv)
#> Loading required package: nlme
#> 
#> Attaching package: 'nlme'
#> The following object is masked from 'package:dplyr':
#> 
#>     collapse
#> This is mgcv 1.8-41. For overview type 'help("mgcv-package")'.

alexpghayes

library(tidyverse)

p_at_least_one_event <- function(p_event, periods = 50) {
  tibble(
    time = 1:periods,
    p_at_least_one_event = 1 - (1 - p_event)^(1:periods)
  )
}

alexpghayes

library(ggplot2)

data(mcycle, package = "MASS")

f_approxfun <- approxfun(mcycle$times, mcycle$accel)
f_splinefun <- splinefun(mcycle$times, mcycle$accel)

mcycle |> 
  ggplot(aes(times, accel)) +
  geom_point() +

alexpghayes

``` r
# pak::pkg_install("stillmatic/MNIST")
library(MNIST)

# 1 is the most common digit in train
table(MNIST::mnist_train$y) / nrow(MNIST::mnist_train)
#> 
#>          0          1          2          3          4          5          6 
#> 0.09871667 0.11236667 0.09930000 0.10218333 0.09736667 0.09035000 0.09863333 
#>          7          8          9 

alexpghayes

library(tidyverse)
library(tidygraph)
library(netmediate)

data <- read.csv("final_regime.IGO.sanction.csv") |> 
  # remove some columns of missing data to avoid downstream issues & unnnecessary columns
  select(-1, -AMCOW, -MOPAN, - year, -version)

node_data <- data |> 
  select(country, ccode, polity2, democracy, sanction) |> 

alexpghayes

library(tidyverse)
library(tidygraph)
library(netmediate)

data <- read_csv("final_regime.IGO.sanction.csv") |> 
  # remove some columns of missing data to avoid downstream issues
  select(-1, -AMCOW, -MOPAN)

node_data <- data |> 
  select(country, ccode, polity2, democracy, sanction)

alexpghayes

``` r
library(tidyverse)
library(glue)
library(unglue)
#> Warning: package 'unglue' was built under R version 4.2.3

"~/../Desktop/patty-restaurants.txt" |> 
  readLines() |> 
  unglue_data("- [{visited}] {name}") |> 
  arrange(visited, name) |> 

alexpghayes

# rotate Y to align it to X
mypro <- function(X, Y) {
  XY <- crossprod(X, Y)
  s <- svd(XY)
  rotation <- s$v %*% t(s$u)
  Yrot <- Y %*% rotation
  diff <- X - Yrot

  colwise_loss <- Matrix::colSums(diff^2)
  two_infty_loss <- max(sqrt(Matrix::rowSums(diff^2)))

alexpghayes

library(tidyverse)
library(qgam)
library(gratia)
library(furrr)
library(mgcv)

plan(multisession, workers = 5)

hap <- read_csv("https://osf.io/download/kpnjf/")