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我想根据时间序列创建一个预测模型。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。每个月的案例都有一些数字（但是，72 个观察值中有 30 个以上的值为NA。）结果，我想创建一个预测模型来预测 2013 年 12 月 1 日之后的未来 3-4 个月的案例？谁能帮我？

这是输出dput(my data)

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")

预先感谢您的贡献。

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1 回答 1

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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。此处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，其中病例是自第一次观察以来的天数和一年中的月份的函数，因为只是观察数据，看起来计数可能与月份有关，并且随着年份的推移而减少。

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)

结果看起来像这样

于 2014-02-28T05:27:05.563 回答