1384758512_795__232_lecture_7.8

6 handout 1 self study singularity analysis which 2can

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: . 2 x Mariolys y a 18 IX.1 Limit and Comb Laws 2 Marni 2 11 Limit Laws Sophie = . .. Random Structures 20 IX.2 Discrete . . . . b . . and Limit Laws FS: Part C Combinatorial 23 IX.3 Mariolys yn 1 xn (rotating instances of discrete 12 25 IV.5 V.1 IX.4 presentations) Continuous Limit Laws Quasi-Powers and Let’s denote this system by M v = y. 13 30 IX.5 Gaussian limit laws Marni Sophie 14 Dec 10 Presentations Asst #3 Due ˆ Unfortunately, such a and b do not exist, so we try to find another vector v in 2 R that is a best approximation of v in the following sense: ˆ ||y − M v|| ≤ ||y − M x|| for all x ∈ R2 . If you take the time to do the calculation, you will see that, indeed, Dr. Marni MISHNA, Department of Mathematics, SIMON FRASER UNIVERSITY Version of: 11-Dec-09 n (yi − (a + bxi ))2 ||y − M v|| = i=1 so minimizing ||y − M v|| is equivalent to minimizing the least-square error, as this error is positive and the square root is a monotone function. Roadmap. From now, we will see how to find such a and b (if we work in R2 ), and more generally how to find a best least-square approximation for a linear system in Rn that...
View Full Document

Ask a homework question - tutors are online