data-raw/nail.R

In robjhyndman/fma: Data Sets from "Forecasting: Methods and Applications" by Makridakis, Wheelwright & Hyndman (1998)

nail <- stats::ts(c(168.89, 172.27, 218.71, 188.72, 188.36, 188.36,
163.17, 174.29, 159.77, 163.17, 163.17, 150.63, 134.54, 118.31,
144.15, 183.47, 203.08, 183.32, 168.47, 169.70, 188.36, 197.78,
197.78, 219.75, 216.98, 174.04, 171.19, 160.50, 173.19, 169.08,
130.98, 133.36, 147.33, 131.39, 139.71, 147.49, 138.56, 134.48,
142.89, 145.74, 139.71, 129.06, 124.82, 115.67, 122.47, 129.28,
127.01, 122.47, 124.57, 121.93, 113.09, 99.98, 95.41, 147.84,
134.35, 111.59, 110.64, 101.24, 103.46, 108.95, 88.34, 77.62,
88.14, 105.66, 127.28, 117.29, 120.72, 107.41, 96.59, 92.78,
88.24, 95.68, 115.58, 103.72, 89.43, 78.98, 70.97, 61.20, 60.70,
73.21, 96.70, 81.20, 91.18, 83.28, 67.46, 65.76, 64.07, 64.92,
57.30, 56.45, 56.45, 46.97, 41.69, 37.92, 32.66, 43.55, 60.14,
30.53, 29.57, 49.10, 54.14, 48.63, 41.60, 39.50, 36.29, 36.10,
37.28, 38.86, 39.98, 36.50, 34.66, 33.12, 30.84, 31.48, 28.67,
29.52, 40.81, 48.63, 41.03, 34.91, 35.87, 29.31, 26.73, 30.53,
30.01, 27.61, 26.67, 26.08, 26.81, 26.72, 22.52, 22.30, 25.76,
27.68, 33.62, 32.87, 27.61, 33.19, 31.37, 30.41, 31.21, 29.72,
26.86, 25.30, 24.87, 27.18, 30.55, 30.51, 36.91, 39.27, 40.20,
40.70, 40.94, 42.44, 43.43, 46.61, 50.06, 52.02, 51.86, 51.43,
49.44, 48.52, 47.56, 46.05, 45.71, 44.93, 40.91, 39.62, 38.06,
38.90, 39.83, 41.48, 43.04, 42.64, 56.59, 60.47, 57.55, 57.96,
56.40, 55.27, 54.13, 53.16, 53.83, 52.31, 50.86, 49.51, 48.41,
47.36, 47.08, 47.36, 46.70, 45.92, 45.19, 44.64, 44.14, 43.45,
42.20),s=1800,f=1)
usethis::use_data(nail, overwrite=TRUE)