Introduction
I PROGRAMMING IN R
1 Review of R Programming
2 Higher Order Functions
3 Recursive Functions
II EFFICIENT DATA PROCESSING AND COMPUTATION
4 Measuring Program Performance
5 Measuring Program Complexity
6 Optimizing Program Performance
7 Querying databases in SQL
III SIMULATIONS AND RESAMPLING METHODS
8 Random Number Generation
9 Monte Carlo Integration
10 Designing Monte Carlo Experiments
11 Bootstrapping and Resampling Methods
IV Other Computing Intensive Methods
12 Cross-Validation
13 Bootstrap Resampling in Modelling
14 Optimization Algorithms
15 Backfitting Algorithm
- 15.0.1 References
UP School of Statistics
© Siegfred Roi Codia

STAT 142: Introduction to Computational Statistics

Chapter 15 Backfitting Algorithm

15.0.1 References

Much of the content of this chapter is derived from materials of Asst.Prof. Michael Van Supranes.

© 2025 Siegfred Roi L. Codia. All rights reserved.