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SoCal RUG - Introduction to Stochastic Processes

Sharpen your data science skills with this is a hands-on workshop on stochastic processes

What is a stochastic processes? The word stochastic is jargon for random. A stochastic process is a system which evolves in time while undergoing chance fluctuations. We can describe such a system by defining a family of random variables, ${X_t}$, where $X_t$ measures, at time t, the aspect of the system which is of interest. For example, $X_t$ might be the number of customers in a queue at time $t$. As time passes, customers will arrive and leave, and so the value of $X_t$ will change. At any time $t$, $X_t$ takes one of the values 0, 1, 2,...; and $t$ can be any value in a subset of $(−\infty, \infty)$, the infinite past to the infinite future.

About this Event

In this workshop, we will talk about a variety of stochastic process models, give their definitions. We will discuss the underlying assumptions and theory for the models. Then we will then explore what types of problems they solve for and practical applications where they are used. This course will cover the following stochastic process models, Markov Chain, Random Walk, Poisson Process, Birth-and-Death Process, Branching Process, and Brownian Motion.

The workshop is designed to be hands-on. Participants are required to bring laptops and be ready to write R, analyze data and interpret results. For each model, we present an example with a complete R code, and then an exercise to work on. Workshop participants do not need to be experts in R, the exercises generally require you to run a few functions that are given in the example problem.

The material covered by the workshop will be taken from my recently published book Stochastic Processes with R, CRC Press, 2022.

Biography of Dr. Olga Korosteleva

Dr. Olga Korosteleva, is a professor of Statistics at the Department of Mathematics and Statistics at California State University, Long Beach (CSULB). She received her Bachelor’s degree in Mathematics in 1996 from Wayne State University in Detroit, and a Ph.D. in Statistics from Purdue University in West Lafayette, Indiana, in 2002. Since then she has been teaching mostly Statistics courses in the Master’s program in Applied Statistics at CSULB, and loving it!

Dr. Olga is an undergraduate advisor for students majoring in Mathematics with an option in Statistics. She is also the faculty supervisor for the Statistics Student Association. She is also the immediate past-president of the Southern California Chapter of the American Statistical Association (SCASA). Dr. Olga is the editor-in-chief of SCASA’s monthly eNewsletter and the author (co-author) of five statistical books.

Event Details

When: February $11^{th}$, 2023

  • Saturday: 8:30 AM - 04:30 PM

Where:

University of California, Irvine -- Paul Merage School of Business

4293 Pereira Drive

Irvine, CA 92617

Registration

Rules

WiFi Access

  • Connect to SSID: UCI Guest
  • Agree to the terms of service

If you are at the Paul Merage Business School you can get help at: Merage Technology Support

4293 Pereira Dr

SB1 - Suite 2400

Irvine, CA 92697

(949)824-4357

Otherwise call the OIT support line at (949) 824-2222 option 3

GitHub Repo

SoCal RUG GitHub Repo: https://github.com/socalrug/

Please install git and clone the following repo before the event. Pull before the start of the event

command:

git clone https://github.com/socalrug/stochastic_processes_2023-02-11.git

Event Repo: https://github.com/socalrug/stochastic_processes_2023-02-11

An alternative approach if you are not comfortable with git is to download a zip file of the repo. However, this approach requires you to download it each time there is a change.

Slack Channel

A slack channel has been set up for the event. This will be used for general announcements but it is also a great source for you to ask questions to other participants.

If you have not created an account on our slack group, create one using the following link:

Slack Group Sign-up

Once you have an account, sign in (you can do it on a web browser or download an app on your phone or desktop).

Slack channel: https://tinyurl.com/socalrug-slack

The channel for the course is stochastic-2023

Check your setup

Since this event depends on you have an R setup that is functional with the correct packages and version of R, we highly recommend that you run the check_setup.r before the event. If you have issues, please reach out to us in the slack channel (see above) to get help.

Posit Cloud

You could use the Posit Cloud during the course instead of setting up RStudio and GitHub. There is a Posit project which will allow you to run RStudio in the cloud. It is preconfigured with the example and exercise code. Plus, it has all the required packages installed. You will need a Posit Cloud account. A free account can be set up.

Twitter

Please follow us on twitter, oc_rug, and also tweet about the event with the hash tag #SoCalRUG

Resources

  • RStudio Cheat Sheets

    • 1-page note sheets covering data science fundamentals and useful R packages.

  • R for Data Science

    • Comprehensive book on the complete data science workflow, including data importing/cleaning, visualization, and data analysis
    • Focus on tidyverse packages
    • Accessible for beginners who have a basic grasp of R

  • Tidyverse, Main Site

    • This is the hub website for the core tidyverse packages
    • Check out the Packages section and associated links for helpful information on using the packages.

  • Advanced R, 2nd Edition

    • This book digs into the details of R.
    • A great resource for more advanced users wanting to learning more about R under the hood.
    • There is also a 1st Edition of the book.

Food

Food, drinks and snacks will be provided throughout the event. We will have vegetarian options available. Please feel free to bring any additional food for yourself if you would like to supplement the meals or if you have other specific dietary constraints.

  • Saturday

    • Lunch: Boxed sandwich

  • Snacks and Drinks

    • Coffee
    • Soft drinks
    • Water
    • Various snacks, (e.g. fruit, chips, nuts, granola bars)
Qty Description Comment
0 Bavarian Ham and Swiss on a Pretzel Roll
12 Roast Beef with Tarragon Horseradish Spread on Wheatberry Bread
12 Shawarma Chicken Ciabatta with Sliced Cucumber, Feta Cheese, Lettuce, Tomato and Lemon Tahini Dressing
10 Mozzarella, Red Pepper, Balsamic and Kale Ciabatta Vegetarian
10 Portobello Banh Mi Sub with Pickled Veggies, Jalapenos and Vegan Sriracha Mayo Vegetarian

Schedule

Start End Activity Slides Location
08:30 08:45 Computer Setup (getting on the network can be a challenge) SB1 2100
08:45 08:50 Introduction SB1 2100
08:50 10:50 Markov Chain 4-29 SB1 2100
10:50 11:05 Break
11:05 12:00 Random Walk 30-44 SB1 2100
12:00 01:00 Lunch Patio
01:00 01:40 Poisson 45-63 SB1 2100
01:40 02:20 Birth-and-death 64-80 SB1 2100
02:20 03:00 Branching Process 81-90 SB1 2100
03:00 03:15 Break
03:15 04:15 Brownian Motion 91-107 SB1 2100
04:15 04:30 Wrap-up SB1 2100