从时间序列预测？

Question

我想从时间序列中创建一个预测模型。我有一个数据框，其中包括2列（日期和案例）。日期列从2008-01-01到2013-12-01。案例每个月有一些数字（但是，72个观察中有30个以上的值NA。）因此，我想创建一个预测模型来预测2013年后3-4个月的案例 - 12-01？谁能帮我？

以下是dput(my data)

的输出

structure(list(Date2 = structure(c(13879, 13910, 13939, 13970, 
14000, 14031, 14061, 14092, 14123, 14153, 14184, 14214, 14245, 
14276, 14304, 14335, 14365, 14396, 14426, 14457, 14488, 14518, 
14549, 14579, 14610, 14641, 14669, 14700, 14730, 14761, 14791, 
14822, 14853, 14883, 14914, 14944, 14975, 15006, 15034, 15065, 
15095, 15126, 15156, 15187, 15218, 15248, 15279, 15309, 15340, 
15371, 15400, 15431, 15461, 15492, 15522, 15553, 15584, 15614, 
15645, 15675, 15706, 15737, 15765, 15796, 15826, 15857, 15887, 
15918, 15949, 15979, 16010, 16040), class = "Date"), Cases = c(16352L, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 10L, NA, 23L, 138L, NA, 18L, 
NA, 3534L, 43L, NA, 3L, 118L, NA, 172L, 4194L, NA, 9L, 2L, 162L, 
NA, 112L, 115L, NA, NA, 119L, NA, NA, 172L, NA, 25L, NA, NA, 
11L, 4L, 457L, 56L, NA, 148L, 446L, 30L, NA, NA, NA, NA, NA, 
NA, NA, 583L, NA, 180L, 193L, NA, 77L, NA, 18L, 15L, NA, NA, 
1L, NA, NA, NA)), .Names = c("Date2", "Cases"), row.names = c(NA, 
-72L), class = "data.frame")

提前感谢您的贡献。

Answer 1

也许这可以让你开始，但做出预测很难，需要很好地理解你的数据。这里提供的信息不足以做出良好的预测IMO。这是一个广义线性模型，其中案例是自第一次观察以来的天数和一年中的月份的函数，因为仅仅看到它看起来像计数的数据可能与月份相关并且随着年份而减少。

library(ggplot2)
dat <- dats[complete.cases(dats),]
dat$days <- dat$Date2 - dat$Date2[1]
mod2 <- glm(Cases ~ days + format(Date2, "%m"), data = dat, family = poisson())
dat$predicted <- "observed"

## See how the model performed against old data
dat <- rbind(dat, data.frame(
    Date2 = dat$Date2,
    Cases = predict(mod2, type = "response"),
    predicted = "predicted",
    days = dat$days))

## predict future cases
futureDates <- seq(as.Date("2014/1/1"), by = "month", length.out = 12)
future <- data.frame(
    Date2 = futureDates,
    days = futureDates - dat$Date2[1])

datFuture <- rbind(dat, data.frame(Date2 = future$Date2,
                             days = future$days,
                             Cases = predict(mod2, type = "response", newdata = future),
                             predicted = "predicted"))

ggplot(datFuture, aes(Date2, Cases, col = factor(predicted), group = predicted)) +
    geom_point(pch = 3) + ylab("Predicted Cases") + xlab("Date") +
    geom_line(lty = 2, lwd = 1.5, alpha = 0.2) +
    geom_smooth(alpha = 0.1, fill = NA)