Blog
Notes and updates on statistics, infectious disease modeling, and other miscellaneous topics.
-
Hierarchical Time Series with hts
Mission The mission is to reproduce the figures in the following article: https://cran.r-project.org/web/packages/hts/vignettes/hts.pdf Load Required Libraries library(hts) Note on Formatting Data This is important to understand in regard to how...
-
Replicating gsynth
Introduction Synthethic methods are a method of causal inference that seeks to combine traditional difference-in-difference types studies with time series cross sectional differences with factor analysis for uncontrolled/ unobserved measures....
-
the power of fake data simulations
This post is basically a self exercise of what Andrew Gelman has already posted here . Fake data simulations are incredible tools to understand your study. It forces you to...
-
a foray into network analysis
Marriage Networks of Florence This post takes the example provided in Kosuke Imai’s Quantitative Social Science: An Introduction . It provides some exploration of network analysis through looking at the...
-
models of microeconomics
I just wanted to explore a little more some of the topics covered in the fantastic Applied Econometrics with R . All of these examples come from their text in...
-
Analysis of Short Time Series
I enjoy reading Rob Hyndman’s blog. The other day he did some analysis of a short times series. More about that is available at his blog here . The neat...
-
make your own api
What’s in an API? An API is an application programming interface. It is basically a set of instructions for interfacing with a server. When working with web data you don’t...
-
Forecasting Benchmarks
Look at this: https://robjhyndman.com/hyndsight/benchmark-combination/ benchmarks <- function(y, h) { require(forecast) # Compute four benchmark methods fcasts <- rbind( N = snaive(y, h)$mean, E = forecast(ets(y), h)$mean, A = forecast(auto.arima(y), h)$mean,...
-
IRT and the Rasch Model
I am inspired by the blog post completed by the team at stitchfix (see details here ) regarding using item response theory for “latent size.” It is a neat approach....
-
Exploring forecast
Time series forecasting is interesting. I want to write more, but not right now. I’m just going to lay out a few functions for explanation later. library(fpp2) library(purrr) library(dplyr) I...