irudnyts

life_table <- read.table(file = "path_to_file/.../life_table.txt", header = T,
                         skip = 2, stringsAsFactors = F)
q_x <- life_table[life_table$Year == 2011, "qx"] # q_x[x + 1] reffers to age x
p_x <- 1 - q_x 
rm(life_table)

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library(copula)
library(stats4)

set.seed(1)

# simulate sample from copula
u <- rCopula(n = 1000, copula = claytonCopula(param = 2, dim = 2))

# simulate marginals
x <- cbind(qnorm(u[, 1], mean = 10, sd = 10), qnorm(u[, 2], mean = 5, sd = 5))

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# WARNING: searches for risk aversion coefficient root assuming to be in range
# 0.01 and 1000

markowitz_portfolio <- function(means, sds, corr,
                                fixed = c("mean", "variance", "lambda"),
                                fixed_level) {
    
    fixed <- match.arg(fixed)
    n <- length(means)
    one <- rep(1, n)

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# library("ggplot2")
# library(reshape2)


adjust_data <- function(vector, name, na_list) {
    vector <- clean_data(vector = vector, na_list = na_list)
    
    frequencies <- numeric(5)
    for(i in seq_along(vector)) {
        frequencies[vector[i]] <- frequencies[vector[i]] + 1

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library(readxl)
library(xtable)

excel2latex <- function(path, sheet = 1, col_names = TRUE, col_types = NULL,
                        na = "", skip = 0) {
    data <- readxl::read_excel(path = path, sheet = sheet,
                               col_names = col_names, col_types = col_types,
                               na = na, skip = skip)
    browser()
    output <- print(xtable(data, digits = 5), include.rownames = FALSE)

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country_continent <- c(
    AD= "Europe",
    AE = "Asia",
    AF = "Asia",
    AG = "North America",
    AI = "North America",
    AL = "Europe",
    AM = "Asia",
    AN = "North America",
    AO = "Africa",

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string <- "Maximize
 obj: x1 + 2 x2 + 3 x3 + x4
Subject To
c1: - x1 + x2 + x3 + 10 x4 <= 20
c2: x1 - 3 x2 + x3 <= 30
c3: x2 - 3.5 x4 = 0
Bounds
0 <= x1 <= 40
2 <= x4 <= 3
General

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library("rvest")
library("stringr")


base_url <- "http://www.artemis.bm"
url <- "http://www.artemis.bm/deal_directory/"

links <- paste0(base_url,
                read_html(url) %>%
                    html_nodes(".table-style01 a") %>%

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library("ggplot2")

log_alm <- read.csv(file = "/Users/irudnyts/Documents/projects/data/alm_logs.csv",
                    stringsAsFactors = FALSE)

exercises <- as.Date(c("2016-10-18", "2016-11-02", "2016-11-16", "2016-12-07"))
before_exercises <- exercises - 7
midterm <- as.Date("2016-11-23")

colnames(log_alm) <- tolower(colnames(log_alm))

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library("ggplot2")
library("gridExtra")

set.seed(1)

x <- runif(min = 0, max = 100, n = 20)
y <- x + rnorm(20, sd = 20)

fit <- lm(y ~ x)