@@ -57,6 +57,27 @@ fig <- fig %>% layout(xaxis = list(title = 'Displacement (cu.in.)'),
5757fig
5858```
5959
60+ ### Plotting Forecast Objects
61+
62+ ``` {r}
63+ library(plotly)
64+ library(forecast)
65+
66+ fit <- ets(USAccDeaths)
67+ fore <- forecast(fit, h = 48, level = c(80, 95))
68+
69+ fig <- plot_ly()
70+ fig <- fig %>% add_lines(x = time(USAccDeaths), y = USAccDeaths,
71+ color = I("black"), name = "observed")
72+ fig <- fig %>% add_ribbons(x = time(fore$mean), ymin = fore$lower[, 2], ymax = fore$upper[, 2],
73+ color = I("gray95"), name = "95% confidence")
74+ fig <- fig %>% add_ribbons(x = time(fore$mean), ymin = fore$lower[, 1], ymax = fore$upper[, 1],
75+ color = I("gray80"), name = "80% confidence")
76+ fig <- fig %>% add_lines(x = time(fore$mean), y = fore$mean, color = I("blue"), name = "prediction")
77+
78+ fig
79+ ```
80+
6081### Loess Smoother with Uncertainty Bounds
6182
6283``` {r}
@@ -83,26 +104,7 @@ fig <- fig %>% layout(xaxis = list(title = 'Displacement (cu.in.)'),
83104fig
84105```
85106
86- ### Plotting Forecast Objects
87-
88- ``` {r}
89- library(plotly)
90- library(forecast)
91-
92- fit <- ets(USAccDeaths)
93- fore <- forecast(fit, h = 48, level = c(80, 95))
94-
95- fig <- plot_ly()
96- fig <- fig %>% add_lines(x = time(USAccDeaths), y = USAccDeaths,
97- color = I("black"), name = "observed")
98- fig <- fig %>% add_ribbons(x = time(fore$mean), ymin = fore$lower[, 2], ymax = fore$upper[, 2],
99-
67BD
color = I("gray95"), name = "95% confidence")
100- fig <- fig %>% add_ribbons(x = time(fore$mean), ymin = fore$lower[, 1], ymax = fore$upper[, 1],
101- color = I("gray80"), name = "80% confidence")
102- fig <- fig %>% add_lines(x = time(fore$mean), y = fore$mean, color = I("blue"), name = "prediction")
103107
104- fig
105- ```
106108
107109#Reference
108110
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