代做PSTAT 160A: Stochastic Process: Fall 2024代做迭代

日期：2024-12-23 10:23

PSTAT 160A: Stochastic Process: Fall 2024

Syllabus

Lectures Time and Location

• Monday, Wednesday (Section 100): 2:00-3:15 PM BUCHN 1920;

• Monday, Wednesday (Section 200): 5:00-6:15 PM HSSB 1173.

•  The lectures will be in-person only, unless stated otherwise.

Note that there will be no recordings of the lectures available.

Office Hours (tentative)

• Tuesday 11 AM-1:00 PM at Room No: 5505 (or Sobel seminar room), South Hall.

• Meetings can be scheduled by appointment via email at pvellais@ucsb .edu.

Teaching Assistants

2-3:15 PM Session

Section	day	Time	Room	Name	Email
44461	R	12-12:50 PM	ILP4105	Mingzhu He	mingzhuhe@ucsb.edu
44469	R	01-1:50 PM	ILP4211	Mingzhu He	mingzhuhe@ucsb.edu
44487	R	02-2:50 PM	GIRV 2127	Juan M Becerra	[email protected]

5-6:15 PM Session
Section day	Time	Room	Name	Email
44503      T	3-3:50 PM	ILP4105	Juan M Becerra	[email protected]
44511      T	4-4:50 PM	ILP3314	MengruiZhang	mengrui@ucsb.edu
44527      T	5-5:50 PM	ILP4209	MengruiZhang	mengrui@ucsb.edu

TA Office Hours

• Mingzhu He : Thursday, 2:00 to 4:00 PM, Building 434, Room 113.

• Juan M Becerra :Thursday, 12:00 to 2:00 PM, Building 434, Room 113.

• MengruiZhang : Tuesday, 2:00 to 4:00 PM, W. South Hall, Room No. 5341.

Prerequisites

PSTAT 120A, PSTAT 120B which serve as the foundation for probability and statistics.

Course Website

Everything related to this course will be posted on Canvas PSTAT 160A-F24.

Textbook

The required textbook is “Introduction to Stochastic Processes with R" by Robert P. Dobrow.  The free electronic copy is available in the UCSB digital library.  Some assignments will be assigned from this book.

Grading Breakdown

• Assignments: 20%

• Quizzes: 20%

• Midterm: 25%

• Final Exam: 35%

Assignments

•  There will be 5 assignments.  No coding is requested in assignments.  Assignments will be posted on Canvas as the course progresses and you will be given sufficient time to complete each of them (see the deadline details on each assignment).  All assignments need to be sub- mitted via Gradescope.

•  Grading: The total score for each assignment is 40 points. Two problems in each assignment will be randomly chosen and graded based on their correctness (10 points each), while credit for completeness will be given for the remaining problems. The lowest assignment score will be dropped.

•  Late Submission Policy:  Late submission can be accepted within 2 days after the deadline with a 20% late penalty. No assignments will be accepted after this period.

Quizzes/Tests

•  There will be 3 quizzes and the lowest quiz score will be dropped. Each quiz takes about 15 minutes (at the end of the lecture), and has a total score of 20 points. The Mid-term test will be for 75 minutes (no lecture on that day) and carries 50 points. They are designed to test your knowledge and understanding of the basic concepts and methods discussed in the lectures.

Quiz/Test	During	Date	Syllabus	Duration	Points
Quiz-1	Lecure 4	Oct. 9 (Wed)	Lect 1-2	15 Min	20
Mid-Term	Lecure 9	Oct. 23 (Wed)	Lect 1-6	75 Min	50
Quiz-2	Lecure 13	Nov. 6 (Wed)	Lect 7-10	15 Min	20
Quiz-3	Lecure 17	Nov. 25 (Mon)	Lect 11-14	15 Min	20
Final (2-3:15 pm)	4:00-6:00	Dec. 9 (Mon)	Lect 1- 19	120 Min	70
Final (5-6:15 pm)	7:30-9:30	Dec. 10 (Tues)	Lect 1- 19	120 Min	70

Note: The Mid-term test and the final exam are cumulative. There will be no make up quiz or test.

Contents to be Covered

•  Probability Review:  Conditional Probability, Random variables, Distributions,  Conditional Expectation, Limit Theorems, Moment Generating Functions. (Chapter 1 & Appendix B)

• Markov Chains: First Steps (Chapter 2)

• Markov Chains: Long-Term Behavior (Chapter 3)

• Counting Processes: Poisson Process (Some Parts of Chapter 6).

Note: Some aspects (parts of Chapter 5) on Markov Chain Monte Carlo (MCMC) methods will be discussed, if time permits.