3inar

#include <stdio.h>

void put_character(char);
void end_line();

char mask_bit(char, char);

int main() {
    char a_character;
    a_character =  -5;

3inar

#include <stdio.h>

void put_character(char);

char mask_bit(char a_char, char bit);

void end_line() {
    printf("\n");
}

3inar

#include <stdio.h>

void put_character(char);

int main() {

    put_character(5);
    end_line();
    return 0;
}

3inar

library(mice)

# y is function of x
x <- rnorm(100)
y <- x + rnorm(100, sd=.5)

# make some ys missing
y[sample(length(y), 10)] <- NA

dframe <- data.frame(y=y, x=x)

3inar

library(dplyr)

data_url <- "https://github.com/3inar/crime_rates/raw/master/src/data/norwegian_crime.rda"

load(url(data_url))

violent <- norwegian_crime %>% filter(crime_type=="¬ Vold og mishandling", year==2014)
violent <- violent %>% mutate(rate=reports/population)

hist(violent$rate)

3inar

# source:
# https://en.wikipedia.org/wiki/List_of_United_States_federal_funding_gaps

budget_gaps <- matrix(c(
  12, 0,
  14, 0,
  10, 0,
  10, 0,
  19, 0,
  13, 0,

3inar

library(ProjectTemplate); load.project()
library(plyr)

crime_type <- "¬ Vold og mishandling"

towns <- mean_crimes(crime_type)
counts <- simulate_crimes(towns$population, towns$cpp, law="binomial")
data <- tibble(rate=counts/towns$population, population=towns$population, reports=counts)
data <- as.tibble(cbind(data, stats(data)))

3inar

library(plyr)
library(MASS)

test <- raply(50000, {
  dat <- mvrnorm(200, mu = c(0,1), Sigma = matrix(c(1,.3,.3,1), nrow=2))
  y <- dat[,1]
  x <- dat[,2]
  
  # throw away most of the data, introduce huge bias
  y <- y[x > 1]

3inar

library(pmadsim)
library(curveselection)
library(plyr)
library(ktspair)


lambdas <- 1/seq(0.01, 2, length.out = 10)
res <- aaply(lambdas, 1, function(lambda2) {
  raply(1000, {
    d <- simulation(lambda2=lambda2)

3inar

expression <- exprs(gene_expression)
expression_se <- se.exprs(gene_expression)
detection <- detection(gene_expression)
control_data <- controlData(gene_expression)

write.csv(expression, file="for_submission/expression.csv")
write.csv(expression_se, file="for_submission/expression_se.csv")
write.csv(detection, file="for_submission/detection.csv")
write.csv(control_data, file="for_submission/control_data.csv")