khakieconomics

Keybase proof

I hereby claim:

• I am khakieconomics on github.
• I am javage (https://keybase.io/javage) on keybase.
• I have a public key ASCOfa5tiUHOtFlCuiaEWO_BO1GQwq0-7ugZRerDYO_p7go

To claim this, I am signing this object:

khakieconomics

# A simple script to grab github commits for a list of users and plot
# Group average commits per day for two groups
# To use this script, you'll need to set up a yaml file with credentials
# for github, and set up a google sheet with columns `Github handle` and 
#`Attended` (with values "Yes" or "No")

# Author: Jim Savage, Schmidt Futures

# Load libraries
library(tidyverse); library(httr); library(yaml);library(jsonlite);

khakieconomics

data {
  int N;
  int N_neg;
  int N_pos;
  int P;
  matrix[N, P] X;
  matrix[N, 3] Y_raw; // first column is 0s and 1s
  int pos_neg[N_neg];
  int pos_pos[N_pos];
}

khakieconomics

data {
  int N; // number of individuals
  int T; // number of time periods
  matrix[N, T] Y; // outcome matrix; missing entries set to -9.0
  int K; // rank of matrix
}
parameters {
  matrix[N, K] M; // individual loadings
  matrix[T, K] U; // time factors
  real<lower = 0> sigma; // error scale

khakieconomics

functions {
  matrix make_pairwise_logit_mat(vector theta) {
    matrix[rows(theta), rows(theta)] out;
    
    for(r in 1:rows(out)) {
      for(c in 1:r) {
        if(r==c) {
          out[r, c] = 0;
        } else {
          out[r, c] = exp(theta[c])/(exp(theta[c]) + exp(theta[r]));

khakieconomics

data {
  int N; // number of observations
  int T; // number of time periods
  int I; // number of groups
  int P; // number of controls
  int<lower = 1, upper = T> time[N]; // time index
  int<lower = 1, upper = I> group[N]; // group index
  vector[N] Y;
  matrix[N, P] X; // you should include group/time means in X
}

khakieconomics

---
title: "Demo of mouse-over"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
---

```{r setup, include=FALSE}
library(flexdashboard)

khakieconomics

library(tidyverse); library(rstan)

# Some fake data

Individuals <- 1000
Sims <- 1000
Months <- 20


initial_values <- data.frame(customer_id = 1:Individuals, initial_value = rnorm(Individuals))

khakieconomics

library(tidyverse); library(lfe)

some_data <- expand.grid(time = 1:10, individual = 1:200) %>% 
  left_join(data_frame(time = 1:10, time_effects=  rnorm(10))) %>% 
  left_join(data_frame(individual = 1:200, individual_effects=  rnorm(200))) %>% 
  mutate(treatment = sample(0:1, n(), replace = T),
         outcome = time_effects + individual_effects + 1 * treatment + rnorm(n())) %>% 
  group_by(time) %>% 
  mutate(demeaned_outcome = outcome - mean(outcome),
         demeaned_treatment = treatment - mean(treatment)) %>% 

khakieconomics

library(rstan); library(tidyverse)

# A utility function
extract_pars <- function(mle_fit, pars) {
  unlist(lapply(pars, function(n) mle_fit$par[grepl(pattern = n, x = names(mle_fit$par))]))
}

# Simulate fake data ------------------------------------------------------