mkiang

# See https://github.com/mkiang/OpenSEIR for comments or updates.
library(shiny)
library(deSolve) 
library(ggplot2)

shinyServer(function(input, output) { 
    
    # Define the SEIR model for open population
    # b is transmission probability, k is contact rate, r is recovery rate,
    # bd is birth/death rate, and L is the rate from latent to infectious.

mkiang

##  Side project name: Boston winters for the last ten years
##  Author: M Kiang
##  Data: http://www.ncdc.noaa.gov/snow-and-ice/daily-snow/
library(ggplot2)
library(dplyr)
library(tidyr)
# library(scales)
# library(gridExtra)
# library(directlabels)

mkiang

##  Side project name: Refilling MTA cards (March 2015 rates)
##  Author: Mathew Kiang
##  See: http://mathewkiang.com/2015/03/23/new-metrocard-rates-and-the-dreaded-dead-zone-of-change/
library(ggplot2)

##  Define parameters
price <- 2.75
bonus <- 1.11
lim   <- 0.15   # amount of change willing to tolerate
upp   <- 25     # upper limit to amount deposited

mkiang

library(microbenchmark)
library(ggplot2)
library(dplyr)

holder <- NULL
endpoints <- 10 ^ (1:9)
for(endpoint in endpoints) {
    x <- microbenchmark(
            seq_len = seq_len(endpoint),
            colon = 1:endpoint, 

mkiang

## Code for this blog post:
## http://mathewkiang.com/2016/10/08/a-visual-tour-of-my-publications/

## Imports
library(RColorBrewer)
library(ggplot2)
library(dplyr)
library(devtools)
devtools::install_github("jkeirstead/scholar")
library(scholar)

mkiang

import requests
import errno
import pandas as pd
import os


def mkdir_p(path):
    """ If a directory does not exist, create it. """
    try:
        os.makedirs(path)

mkiang

## Code for this blog post:  https://mathewkiang.com/2017/01/16/using-histogram-legend-choropleths/

## Download the drug death data from:
## https://blogs.cdc.gov/nchs-data-visualization/drug-poisoning-mortality/
## 
## Download the 2013 CB shapefiles (500k will do) for counties and states:
## https://www.census.gov/geo/maps-data/data/cbf/cbf_counties.html
## https://www.census.gov/geo/maps-data/data/cbf/cbf_state.html

## Imports ----

mkiang

#SIR practical from Debarre and Bonhoeffer ("SIR models of epidemics")
library(deSolve)

parms <- c(beta = 0.333, k = 3 , r = 0.333)
inits <- c(S = 499, I = 1, R = 0)
dt <- seq(0, 300, 1)

SIR <- function(t, x, parms){
    with(as.list(c(parms, x)), {
        

mkiang

## Code for the blog post here: 
## https://mathewkiang.com/2017/10/08/using-r-wikipedia-sherparomeo-show-new-england-journal-medicines-pre-print-statement-empirically-false
## You can download the original files from the blogpost.
## If downloading new files, you probably want to change the date in the file names.

## Imports
library(rvest)
library(tidyverse)

## Wiki data

mkiang

Keybase proof

I hereby claim:

• I am mkiang on github.
• I am mkiang (https://keybase.io/mkiang) on keybase.
• I have a public key ASBcR0WeyXKq1QlGo0lxZxRG2VRNJKIJ8-h6NNFJLDFSYAo

To claim this, I am signing this object: