abikoushi

library(dplyr)
library(MASS)
data("diamonds", package = "ggplot2")
diamonds2 <- dplyr::select(diamonds, carat, depth:price,x:z)

a01 <- rgb(0,0,0,0.1)
png("pairs.png")
plot(diamonds2, col=a01)
dev.off()

abikoushi

library(dplyr)
library(tidyr)
library(ggplot2)
library(patchwork)


df1 <- mutate(iris,id=1:n()) %>% 
  pivot_longer(1:4)

df2 <-reframe(df1, x=c(as.integer(factor(name))-0.25,as.integer(factor(name))+0.25),

abikoushi

scan1_mtx <- function(con, skip = 0){
  base::scan(con, nmax = 1, quiet=TRUE, 
             what = list(i=integer(), j=integer(), v=numeric()),
             skip = skip)
}


dataloader_mtx2 <- function(file_path, bag){
  con <- file(file_path, open = "r") #Open for reading in text mode
  #get matrix size

abikoushi

#include "RcppArmadillo.h"
// [[Rcpp::depends(RcppArmadillo)]]
using namespace Rcpp;
using namespace arma;

// [[Rcpp::export]]
double sumouterprod(const arma::field<arma::vec> & V){
  int K = V.n_rows;
  arma::vec tout = V(0);
  for(int j=1; j<K; j++){

abikoushi

#include "RcppArmadillo.h"
// [[Rcpp::depends(RcppArmadillo)]]
using namespace Rcpp;
using namespace arma;

// [[Rcpp::export]]
double sumouterprod(const arma::field<arma::vec> & V){
  int K = V.n_rows;
  arma::vec tout = V(0);
  for(int j=1; j<K; j++){

abikoushi

library(tweedie)
library(dplyr)
library(ggplot2)
library(ggh4x)

pow <- c(1.01,1.05,1.3,1.9)
phi <- c(0.2,0.5,1,3)
mu <- c(0.1,0.3,2)

dens <- expand.grid(y=y,power=pow,mu=mu,phi=phi) %>% 

abikoushi

\documentclass{beamer}
\usepackage{tikz}
\setbeamertemplate{navigation symbols}{} 
\usetikzlibrary{positioning}
\makeatletter
\usefonttheme{serif}
\usepackage{xcolor}

\def\mathunderline#1#2{\color{#1}\underline{{\color{black}#2}}\color{black}}

abikoushi

library(BiasedUrn)
library(exact2x2)
library(animation)

#MCMCpack::dnoncenhypergeom(x = NA, cs[1],cs[2],rs[1], 1)
saveGIF({
  for(i in c(0:17,17:0)){
    rs <- c(18,17)
    cs <- c(17,18)
    X <-matrix(c(i,cs[1]-i,rs[1]-i,cs[2]-(rs[1]-i)), nrow=2)

abikoushi

x <- seq(-1,1, length.out=100)
x2 <- 1*(x>0)
X <- cbind(x, x2, x*x2)
B <- c(0.5,2,-1)
mu <- c(X%*%B)
set.seed(2024);y <- mu + rnorm(100,0,0.1)

fit <- lm.fit(X,y)
muhat <- c(X%*%c(fit$coefficients))

abikoushi

library(animation)
pvfun <- Vectorize(function(r, y){
  poisson.test(y, T = tau, r = r)$p.value  
})

postprob <- function(r, x, tau){
  pl <- pgamma(r, shape = x+0.5, rate = tau, lower.tail = FALSE)
  pu <- pgamma(r, shape = x+0.5, rate = tau, lower.tail = TRUE)
  2*pmin(pl,pu)
}