使用 dplyr 和 sample_n 根据权重随机抽样

Question

我想根据单独数据框中的索引给出的一组权重随机抽样月份，但索引会根据一些分类变量而变化。

下面是一个示例问题:

require(dplyr)
sim.size <- 1000
# Generating the weights for each month, and category combination
class_probs <- data_frame(categoryA=rep(letters[1:3],24)
                          categoryB=rep(LETTERS[1:2],each=36),
                          Month=rep(month.name,6),
                          MonthIndex=runif(72))


# Generating some randomly simulated cateogories
sim.data <- data_frame(categoryA=sample(letters[1:3],size=sim.size,replace=TRUE),
                       categoryB=sample(LETTERS[1:2],size=sim.size,replace=TRUE))

# This is where i need help
# I would like to add an extra column called Month on the end of sim.data
# That will be sampled using the class_probs data, taking into account the
# Both categoryA and categoryB to generate the weights in MonthIndex
sim.data %>%
  group_by(categoryA,categoryB) %>%
  do(sample_n(class_probs[class_probs$categoryA==categoryA &
                          class_probs$categoryB==categoryB,  ],
              size=nrow(sim.data[sim.data$categoryA==categoryA &
                                 sim.data$categoryB==categoryB]),
              replace=TRUE,
             weight=MonthIndex)$Month)

因此，对于每个组，我希望能够对 categoryA 和 categoryB 的特定组合的相同次数进行采样，并且对于每次出现的情况，我都希望根据 class_prob 数据子集给出的 MonthIndex 对一个月进行采样。框架...

然后将所选月份绑定(bind)到原始数​​据集 sim.data作为额外的列

希望我的代码已经很接近了...我只需要一些帮助来确定需要更改的内容...

Answer 1

这是一种使用辅助函数进行采样的方法，然后是一个简单的 mutate来电dplyr创建新列。

辅助函数:

sampler <- function(x, y, df) {

  tab <- sample_n(df %>% filter(categoryA==x, 
                  categoryB==y),
           size=1,
           replace=TRUE,
           weight=MonthIndex)

  return(tab$Month)

}

调用它来创建一个新变量:

sim.data %>%
  rowwise() %>%
  mutate(month = sampler(categoryA, categoryB, class_probs))

结果:

Source: local data frame [1,000 x 3]
Groups: <by row>

   categoryA categoryB     month
1          b         B  February
2          b         A  February
3          b         B       May
4          c         B  December
5          c         B      June
6          b         A    August
7          c         A     March
8          c         A September
9          b         A    August
10         c         A  December
..       ...       ...       ...