Bruna Wundervald brunaw

💜

working on ML & bayesian stats

brunaw / HEBART Running

Created June 30, 2022 11:31

	# In case you're installing, building, or removing the package:
	# remove.packages("hebartBase")
	# devtools::document()
	# devtools::check()
	# devtools::install()

	# Exemplifying:
	# Package loading ----------------------------------
	library(magrittr)
	library(ggplot2)

brunaw / plotting with map + patchwork

Created June 29, 2022 16:58

	library(tidyverse)
	library(patchwork)
	iris_species <- unique(iris$Species)
	colours <- c("pink", "red", "blue")

	plots <- purrr::map2(
	iris_species, colours,
	~{
	p <- iris \|>
	dplyr::filter(Species == .x) \|>

brunaw / hebart_comparison

Created May 9, 2022 16:16

	# Loading packages
	library(tidyverse)
	library(tidymodels)
	library(hebart)
	library(lme4)
	library(dbarts)
	library(patchwork)

	# Loading Andrew's friedman data
	df <- read.table("https://raw.githubusercontent.com/andrewcparnell/rBART/master/friedman.txt")

brunaw / hebart_i=1

Last active May 5, 2022 13:21

	# Loading packages
	library(tidyverse)
	library(hebart)

	df <- read.table("https://raw.githubusercontent.com/andrewcparnell/rBART/master/friedman.txt")
	df$y <- rnorm(nrow(df))
	df$group <- sample(1:5, nrow(df), replace = TRUE)

	group_variable = "group"
	formula <- y ~ V2 + V3 + V4 + V5 + V6

brunaw / create_dat.R

Created October 22, 2021 19:43

	create_dat <- function(artist, track){
	notes = c("A", "B", "C", "D", "E", "F", "G")
	flats = "b"
	minor = "m"
	sharps = "#"
	all_notes = c(notes, paste0(notes, flats), paste0(notes,
	sharps), paste0(notes, minor), paste0(notes, flats, sharps),
	paste0(notes, minor, sharps), paste0(notes, flats, minor),
	paste0(notes, flats, sharps, minor))
	artist <- chorrrds::get_songs(artist)

brunaw / Simulate and evaluate conditional

Last active August 30, 2021 20:49

	library(tidyverse)
	library(MASS)

	det2 <- function(k_1_d, k_2_d, M_d) {
	n <- nrow(M_d)
	n_j <- colSums(M_d)
	tMM <- crossprod(x = M_d)
	Psi_tilde_inv <- diag(n) - M_d%%diag(k_1_d/(1 + k_1_dn_j))%*%t(M_d)
	return(log(k_2_d) + log(1/k_2_d + sum(Psi_tilde_inv)) + sum(log(1 + k_1_d*n_j)))
	}

brunaw / bruna_data_handling

Created April 13, 2021 13:16

brunaw / PCA and k-means data

Created July 14, 2020 15:23

	library(tidyverse)
	library(factoextra)

	agg_transp <- read_csv("data/aggregated_transport.csv")

	transp_border <- agg_transp %>%
	group_by(location) %>%
	mutate(mean_value = mean_value/max(mean_value))

brunaw / RIP data wrangling

Created July 6, 2020 10:26

	library(tidyverse)

	# Read the data
	df <- read_csv("RIP_towns_6May_w_county_edited.csv")

	# Change the format from wide to long
	df_long <- df %>%
	gather(key = date, value = deaths, -Town, -County) %>%
	mutate(year = paste0("20", str_extract(date, "[0-9]{2}")),
	year = as.numeric(year),

Created June 12, 2020 16:25


	eliminate_words <- function(first_sentence, second_sentence){
	if(is.na(second_sentence)) return(first_sentence)

	first_word <- word(second_sentence, 1)
	characters_first_word <- strsplit(first_word, split = "")[[1]]

	# Get all possible words that could have remained in the previous
	# sentence
	words_list <- vector()