generate numbers

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(message = FALSE)

http://www.cookbook-r.com/Numbers/Generating_random_numbers/

library(tidyverse)

seq()

seq(from, to, by)

seq(1, 10, by = pi)

rep()

rep(sequence, each, times, len)

rep(c("a","b"), each = 2)
rep(c("a","b"), each = 2, times = 4)
rep(c("a","b"), each = 2, times = 4, len = 5)

runif()

runif(elements, min, max)
returns floats by default

set.seed(420)
runif(5, 1, 10)
# use floor, ceiling or round to get integers
runif(5, 1, 10) %>% floor()
runif(5, 1, 10) %>% ceiling()

sample()

sample(range, elements, replace?)
can set with or without replacement

set.seed(420)
sample(1:100, 5, replace = TRUE)
sample(1:100, 5, replace = FALSE)

normal functions

http://seankross.com/notes/dpqr/

dnorm

dnorm(x, mean = 0, sd = 1, log = FALSE)

• probability density for the normal distribution
• value = height of PDF of normal distribution

dnorm(0, mean = 0, sd = 1) # default values, dnorm = 0.3989423
zscores = seq(-3,3,by=0.1)
dvalues = dnorm(zscores)
plot(dvalues, # Plot where y = values and x = index of the value in the vector
     xaxt = "n", # Don't label the x-axis
     type = "l", # Make it a line plot
     main = "pdf of the Standard Normal",
     xlab= "Z-score") 

# These commands label the x-axis
axis(1, at=which(dvalues == dnorm(0)), labels=c(0))
axis(1, at=which(dvalues == dnorm(1)), labels=c(-1, 1))
axis(1, at=which(dvalues == dnorm(2)), labels=c(-2, 2))

pnorm

pnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)

• probability distribution
• inverse of qnorm (given zscore, what’s the cumulative probability)
• value = integral (area) from -inf to q of PDF of normal distribution

pnorm(0, 0, 1) # default args, pnorm = 0.5
pnorm(2, 5, 3) # 0.1586553

qnorm

qnorm(p, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)

• quantile function
• inverse of pnorm (given quantile, what’s the zscore?)

qnorm(0.5) # 0
qnorm(0.99) # 2.326348 (zscore of 99th quantile of normal distribution)

rnorm

rnorm(n, mean = 0, sd = 1)

• random deviates
• generates a vector of normally distributed random numbers

rnorm(5, mean = 0, sd = 1) # 1.15572257  0.36096234  0.01558131  0.57173629 -0.85518190

EOF