| library(tidyverse) | |
| input <- readLines("input") | |
| ##### Part 1 ##### | |
| vals <- tibble( | |
| mul = str_match_all(paste(input, collapse = ""), | |
| "(mul\\(\\d{1,3},\\d{1,3}\\))")[[1]][,2]) %>% | |
| mutate(val1 = as.numeric(str_match(mul, "\\((\\d{1,3})\\,")[,2]), | |
| val2 = as.numeric(str_match(mul, "\\,(\\d{1,3})\\)")[,2])) %>% |
| library(tidyverse) | |
| input <- read_delim("input", delim="\t", col_names = "d") | |
| ##### Part 1 ##### | |
| report_safe <- function(report) { | |
| vals <- as.numeric(str_split(report, " ")[[1]]) | |
| difs <- diff(vals) |
| library(tidyverse) | |
| input <- read_delim("input.txt", col_names = c("x", "y"), delim = " ") | |
| #### Part 1 #### | |
| input_ordered <- bind_cols( | |
| x = input$x[order(input$x)], | |
| y = input$y[order(input$y)]) %>% | |
| mutate(dist = abs(x-y)) |
I want to simulate to demonstrate how it's possible that the hierarchical model can even have better power than getting exactly the right values.
Note: The original question and results are no longer applicable due to a few fatal flaws with my code. Below follows the correct code. But the oracle is optimal now...
| library(mgcv) | |
| library(tidyverse) | |
| # Data | |
| BPR <- | |
| tibble::tribble( | |
| ~time, ~bpr, | |
| 50, 0.892042350231095, | |
| 170, 0.888132434012036, |
| library(tidyverse) | |
| library(magick) | |
| # devtools::install_github("thomasp85/patchwork") | |
| library(patchwork) | |
| colours = c("#85d4e3", | |
| "#e39f85") | |
| set.seed(40) |
| # Please note that this script is not fully tested. This is a genericised | |
| # version of two working versions, where I've added and removed bits and | |
| # pieces along the way without testing them. Please let me know if there | |
| # are errors or things missing, because this could easily have happened. | |
| library(tidyverse) | |
| library(googlesheets) | |
| library(lubridate) | |
| library(gmailr) |