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# Francis SmartEconometricsBySimulation

Last active Sep 5, 2019
2019_09_04-Assignment1.md
View gist:fe40ec9f749213d1240011684001dda5

emailto: psteiner@umd.edu student: Francis Smart fsmart@gmail.com EDMS769G

# Text Network graph
#           Student Ability _______________________
#            /           |                         \_____
#          /             |  Public/Private Transport     \
#         ↓              ↓     ↓                          ↘

Last active Apr 14, 2016
View ConsumptionInference.R
 # Estimating Weekly consumption from periodic purchasing data library(dplyr) library(data.table) library(reshape) library(tidyr) library(ggplot2) # Day Purchase
Created Mar 2, 2016
View Campaign-Finance-Density.R
 rm(list=ls()) library(data.table) library(dplyr) library(ggplot2) setwd('Z:/Data/FEC') dsum <- function(...) dplyr::summarize(...) to.data.table <- function(x) {(class(x) <- class(data.table())) ;x}
Last active Mar 2, 2016
View FEC-Clinton-PieCharts.R
 rm(list=ls()) library(data.table) library(dplyr) library(ggplot2) library(scales) setwd('Z:/Data/FEC') dsum <- function(...) dplyr::summarize(...)
Last active Aug 29, 2015
numbers2words
View numbers2words.R
 # adapted from John Fox's numbers2words function require(magrittr); require(Rmpfr) make.digits <- function(x) { # This is a function breaks an input number x into the positive (left) # and negative(right) elements and returns these as numbers x <- toString(x) negative <- substr(x,1,1)=="-" if (negative) x <- substring(x,2)
Created Sep 10, 2014
Easy Bordered Cubes in R
View cubes.R
 library('rgl'); library('magrittr') cube <- function(x=0,y=0,z=0, bordered=TRUE, filled = TRUE, lwd=2, scale=1, fillcol = gray(.95), bordercol ='black', ...) { mycube <- cube3d() # Reduce size to unit
Last active Aug 29, 2015
Analysis of Ebola data
View ebola.R
 # First let's load some libraries require('XML'); require('reshape2'); require('ggplot2') require('magrittr') # See # http://goo.gl/Wj5F87 # I have borrowed Andrie's code from stackoverflow # http://goo.gl/noYVo7 source("http://goo.gl/w64gfp") # Load in the google spreadsheet
Last active Aug 29, 2015
 I recently found myself in need of a function to sample randomly from an arbitrarily defined probability density function. An excellent post by Quantitations shows how to accomplish this using some of Rs fairly sophisticated functional approximation tools such as integrate and uniroot. The only problem with this excellent post was that the machine cost was enormous with samples of 1000 draws taking 10 seconds on my machine and repeated samples of 100,000+ draws (which I was after) clearly being unworkable. Thus I decided to take my own crack at it. First let us review the basics of drawing random variables from non-uniform distributions. The standard method I think most algorithms use works as follows: Assumptions 1. You can draw pseudo-random uniform variable u 2. You can integrate the pdf to construct a cdf $$p = F(x) = \int_{-\infty}^\infty f(x) dx$$ 3. You can invert the cdf in order to solve for p $$G(F(x))=F^{-1}(F(x))=F^{-1}(p)=x$$