HoltWinters on Panel Data

Question

I am trying to run the HoltWinters procedure on panel data to come up with sales forecasts for a list of companies. My data frame has the fields "Company", "Year" and "Sales". I am interested in adding an extra column to this data frame that shows fitted sales obtained using HoltWinters.

For a single company, the exercise is trivial as I can just run HoltWinters. I can extend this approach to my situation by looping across companies, but I am looking for a solution that avoids loops.

Any thoughts?

Answer 1

Reading the help file for HoltWinters, it doesn't look like it can be vectorized, so I don't think that you can avoid loops. The best I can do is to make your loops pretty with lapply (there may also be a small speed gain). Assuming you have the individuals as separate time series (or time series unions):

set.seed(0)
a <- ts(rnorm(10), start=c(2001, 5), freq=12)
b <- ts(rnorm(10), start=c(2001, 5), freq=12)
c <- ts(rnorm(10), start=c(2001, 5), freq=12)
d <- ts(rnorm(10), start=c(2001, 5), freq=12)
e <- ts(rnorm(10), start=c(2001, 5), freq=12)
f <- ts(rnorm(10), start=c(2001, 5), freq=12)
individual.one <- ts.union(a, b, c)
individual.two <- ts.union(d, e, f)
panel <- list(individual.one, individual.two)

ans <- lapply(panel, HoltWinters)

Yields:

> ans
Holt-Winters exponential smoothing with trend and additive seasonal component.

Call:
 FUN(x = X[[1L]])

Smoothing parameters:
 alpha:  0
 beta :  0
 gamma:  0

Coefficients:
            [,1]
a   -0.504984544
b   -0.035336155
s1  -1.085615710
s2  -0.352859142
s3   0.002437573
s4   2.550897907
s5   0.986769568
s6  -0.596066930
s7  -1.028559659
s8  -0.187923905
s9  -0.149289171
s10 -0.168011617
s11  0.606452449
s12 -0.578231362

[[2]]
Holt-Winters exponential smoothing with trend and additive seasonal component.

Call:
 FUN(x = X[[2L]])

Smoothing parameters:
 alpha:  0
 beta :  0
 gamma:  0

Coefficients:
           [,1]
a   -0.39575955
b   -0.04035375
s1   0.75505039
s2  -0.64553006
s3   1.06488778
s4  -0.40487180
s5   1.74515472
s6   0.64324387
s7  -0.36380752
s8  -0.74481981
s9  -1.04726447
s10 -0.90172103
s11 -1.42433355
s12  1.32401148

Where:

> panel
[[1]]
                    a          b           c
May 2001  1.262954285  0.7635935 -0.22426789
Jun 2001 -0.326233361 -0.7990092  0.37739565
Jul 2001  1.329799263 -1.1476570  0.13333636
Aug 2001  1.272429321 -0.2894616  0.80418951
Sep 2001  0.414641434 -0.2992151 -0.05710677
Oct 2001 -1.539950042 -0.4115108  0.50360797
Nov 2001 -0.928567035  0.2522234  1.08576936
Dec 2001 -0.294720447 -0.8919211 -0.69095384
Jan 2002 -0.005767173  0.4356833 -1.28459935
Feb 2002  2.404653389 -1.2375384  0.04672617

[[2]]
                  d          e           f
May 2001 -0.2357066  1.7579031  0.26613736
Jun 2001 -0.5428883  0.5607461 -0.37670272
Jul 2001 -0.4333103 -0.4527840  2.44136463
Aug 2001 -0.6494716 -0.8320433 -0.79533912
Sep 2001  0.7267507 -1.1665705 -0.05487747
Oct 2001  1.1519118 -1.0655906  0.25014132
Nov 2001  0.9921604 -1.5637821  0.61824329
Dec 2001 -0.4295131  1.1565370 -0.17262350
Jan 2002  1.2383041  0.8320471 -2.22390027
Feb 2002 -0.2793463 -0.2273287 -1.26361438