Selection of additive/multiplicative trend/error/seasonality in ETS

Forecasting: principles and practice. This book tells about 30 different types of ETS models. It describes about additive models and multiplicative model. I would like to know on what basis do we decide from our data that trend/seasonality/error is additive or multiplicative.

Example: >dput(x.ts)

structure(c(7632, 6686, 3442, 4556, 7796, 1534, 1466, 3535, 2503,
7534, 1197, 5861, 8846, 7219, 5066, 13177, 7833, 5585, 6392,
5787, 13488, 9413, 7610, 11301, 14912, 13578, 12091, 14628, 10703,
7373, 13638, 10794, 12186, 8137, 7874, 7707, 11569, 13446, 10339,
19086, 15201, 11741, 19368, 15755, 12214, 13859, 13096, 14548,
16191.1, 23122.3, 21421.6, 20904.5, 19711.5, 9481.9, 18699, 21271.9,
19515.5, 19890.6, 16789, 31409.3, 21917.2, 24911.4, 26072.4,
23919.3, 26980.8, 41661.2, 27065.4, NA, NA, NA, NA, NA), .Tsp = c(2010,
2015.91666666667, 12), class = "ts")


After plotting this data we can see trend but no seasonality. Now how do we say that the trend is additive or multiplicative? Also how we select additive or multiplicative error for ETS model?

In short
1.What do you mean by additive and multiplicative trend?
2.What do you mean by additive and multiplicative seasonality?
3.2.What do you mean by additive and multiplicative error?

• Why don't you try reading the book you quote? – Rob Hyndman Jun 27 '16 at 17:56