davharris

library(MASS)
n = 1000

x = mvrnorm(n, c(0, 0), Sigma = matrix(c(1, .9, .9, 1), nrow = 2))

cor(x) # correlation of about 0.9 before thresholding

thresholded.values = x > 0
cor(thresholded.values)  # Correlation drops to about 0.7, depending on random seed

davharris

library(ggplot2)
library(mgcv)

# Something bad happens at t=400 and lambda drops
lambdas = c(runif(4E2, 6, 8), runif(1E2, 2, 4))
obs = rpois(length(lambdas), lambdas)

qplot(x = 1:length(obs), y = obs) + 
  stat_smooth(method = "gam", family = poisson, formula = y ~ s(x), size = 3)

davharris

set.seed(1)

# Create fake data
x = runif(100, 0, 5)
y = .25 * x^3 - x^2 + rnorm(length(x))
data = data.frame(x = x, y = y)

# Identify 500 points to include in the plots
x.sequence = seq(0, 5, length = 500)

davharris

# Install the most recent version of mistnet (if needed) using the devtools package
# devtools::install_github("davharris/mistnet")
library(mistnet)

# Grab a small data set from another package
library(ade4)
data(aviurba)

# Reduce the fauna table to ones and zeros
y = as.matrix(aviurba$fau > 0)

davharris

### Keybase proof

I hereby claim:

  * I am davharris on github.
  * I am harris (https://keybase.io/harris) on keybase.
  * I have a public key whose fingerprint is 0867 7213 63D1 967B 2B0B  E9E6 942D 033F 15ED 4389

To claim this, I am signing this object:

davharris

gnr_resolve("American Crow")

# $results
# submitted_name           matched_name data_source_title score
# 1  American Crow American Painted-snipe               EOL  0.25
# 
# $preferred
# NULL

davharris

n = 7    # Number of elements to permute
k = 1E5  # Number of permutations allowed by RNG

# Declare a character vector to store permutations
permutations = character(k)
for(i in 1:k){
  # save k permutations as strings
  permutations[i] = paste(sample.int(n), collapse = "-")
}

davharris

#Based on https://github.com/robotlolita/fuck-you
# and https://en.wikipedia.org/wiki/Transformation_of_text

screw_you = function(x){
  chars   = strsplit(paste0(c(" ", rev(letters), rev(LETTERS), 0, 9:1, "&_?!\".';'"), collapse = ""), "")[[1]]
  flipped = strsplit(
    " zʎxʍʌnʇsɹbdouɯlʞɾıɥɓɟǝpɔqɐZ⅄XMΛ∩⊥SᴚΌԀONW⅂⋊ſIH⅁ℲƎᗡƆ𐐒∀068ㄥ9ގㄣƐᘔ⇂⅋‾¿¡„,˙'؛", 
    "")[[1]]
  
  split = strsplit(as.character(substitute(x)), "")[[1]]

davharris

# Confirming that I understand how geiger's variance-covariance matrices work

library(geiger)
library(mvtnorm)

geo = get(data("geospiza"))


# Simulate one trait using geiger::sim.char
sim = t(

davharris

f = function(x){
  x
}

f()  # Throws error: x is missing

g = function(x){
  letters[x]
}