**Introduction:**

These are results and code for the
problems and examples found in Chapter 3 of this famous book.

- Functions for Exponential Smoothing:
- simple_exp_smoothing.m (simple exponential smoothing)
- simple_exp_smoothing_optimum.m (finds the optimal relaxation coefficient when performing simple exponential smoothing)
- double_exp_smoothing.m (double exponential smoothing)
- double_exp_smoothing_optimum.m (finds the optimal relaxation coefficient when performing double exponential smoothing)
- triple_exp_smoothing.m (triple exponential smoothing)
- triple_exp_smoothing_optimum.m (finds the optimal relaxation coefficient when performing triple exponential smoothing)

- Examples from the book:
- example_3_4.m (Duplicates Example 3.4 from the book)

- Data sets considered in this chapter:
- load_computer_software_sales.m (loads the computer sales data)
- load_us_lumber.m (loads the US lumber data set)
- load_student_enrollment.m (loads the student enrollment data set)

- Problems:
- prob_3_4.m (simple exponential smoothing of the U.S. lumber data)
- prob_3_8.m (plots the forecast weights for the one and two-step ahead)
- prob_3_9.m (implements Holt's method and double exponential smoothing)
- prob_3_10.m (computes the variance scale factor for various look-aheads)
- prob_3_14.m (implements simple/double/triple exponential smoothing on the computer software sales)

John Weatherwax Last modified: Sun May 15 08:46:34 EDT 2005