Papers authored/co-authored by Kim Feb 10, 2019 Estimating Effects of Passenger Dwell and Non-Passenger Delay on Overall Bus Trip Time: A Hierarchical Modeling Approach August 2018 For local bus service, in-vehicle travel time is composed of time spent in motion and time stopped. Time in motion is dependent on factors common to general traffic travelling on a road segment, while time stopped has some features in common with general traffic (i.e., traffic signals) and some unique to buses such as passenger dwell time.

Shiny Apps authored by Kim Sep 22, 2018 Travel Behavior Inventory Onboard Survey Visualization: This Shiny application serves as a tool for exploring the survey data. Visualizations include bar plots, interactive maps, heat maps, and sankey diagrams.

About Me Sep 9, 2018 I am currently working as a data scientist at the Federal Reserve Bank of Minneapolis, Community Development Division. My background is in Economics and Statistics. I received my B.A. in Economics and Statistics from Macalester College. I am currently pursuing an M.S. in Statistics at the University of Minnesota as a part-time student. I have had professional experience in economic consulting, public transportation, healthcare, marketing and community development. When I am not working, I host meetups and plan conferences.

Introduction to data.table Oct 11, 2018 This week, I had the opportunity to present R data.table package to R Ladies Twin Cities meetup. With the help of another R Lady, Haema Nilakanta, we put together this tutorial on the package. This document was originally published on RPubs here. This document is by no means exhaustive. However, it is a good start for those who would like to get introduced to data.table. Overview What is data.table? “data.table is an R package that provides an enhanced version of data.

Bus Speed Visualization Sep 21, 2018 1 Data 2 Speed Calculation 3 Speed Visualization 4 Wrapping Up Note: This post is based on one of the projects I did during my tenure at Metro Transit. You can find a copy of a BitBucket repository containing functions used in this post here. Disclaimer: Opinions and comments expressed are solely my own and do not express the views or opinions of Metro Transit. Within the past couple decades, many transit agencies across North America and all over the world have started to collect location records of every bus using the Automatic Vehicle Location (AVL) technology.