Question

我想对面板数据进行分区并保留数据的面板性质：

      library(caret)
      library(mlbench)

      #example panel data where id is the persons identifier over years
      data <- read.table("http://people.stern.nyu.edu/wgreene/Econometrics/healthcare.csv",
                    header=TRUE, sep=",", na.strings="NA", dec=".", strip.white=TRUE)

      ## Here for instance the dependent variable is working
      inTrain <- createDataPartition(y = data$WORKING, p = .75,list = FALSE)

      # subset into training
      training <- data[ inTrain,]
      # subset into testing
      testing <- data[-inTrain,]
      # Here we see some intersections of identifiers 
      str(training$id[10:20])
      str(testing$id)

但是我想在分割或采样数据时，避免将同一个人（id）分成两个数据集。这是一种从数据中随机采样/分区的方法，将不同的分配给相应的分区而不是观察？

我试图采样：

    mysample <- data[sample(unique(data$id), 1000,replace=FALSE),]

然而，这会破坏数据的面板性质......

Answer 1

我认为使用sample()的抽样方法存在一个小问题：它使用id变量，就像行号一样。相反，该函数需要获取属于ID的所有行：

nID <- length(unique(data$id))
p = 0.75
set.seed(123)
inTrainID <- sample(unique(data$id), round(nID * p), replace=FALSE)
training <- data[data$id %in% inTrainID, ] 
testing <- data[!data$id %in% inTrainID, ] 

head(training[, 1:5], 10)
#    id FEMALE YEAR AGE   HANDDUM
# 1   1      0 1984  54 0.0000000
# 2   1      0 1985  55 0.0000000
# 3   1      0 1986  56 0.0000000
# 8   3      1 1984  58 0.1687193
# 9   3      1 1986  60 1.0000000
# 10  3      1 1987  61 0.0000000
# 11  3      1 1988  62 1.0000000
# 12  4      1 1985  29 0.0000000
# 13  5      0 1987  27 1.0000000
# 14  5      0 1988  28 0.0000000


dim(data)
# [1] 27326    41
dim(training)
# [1] 20566    41
dim(testing)
# [1] 6760   41
20566/27326
### 75.26% were selected for training

让我们检查班级余额，因为createDataPartition会使所有组中的WORKING的班级余额相等。

table(data$WORKING) / nrow(data)
#         0         1 
# 0.3229525 0.6770475 
#
table(training$WORKING) / nrow(training)
#         0         1 
# 0.3226685 0.6773315 
#
table(testing$WORKING) / nrow(testing)
#         0         1 
# 0.3238166 0.6761834 
### virtually equal

Answer 2

我想我会为任何关注此问题的人指出插入符号的groupKFold函数，这对于此类数据的交叉验证非常有用。从documentation： “要基于组拆分数据，可以使用groupKFold：

SELECT id, texto
FROM test3_sim
WHERE MATCH (texto) AGAINST ('NA' IN BOOLEAN MODE)
AND texto is not null

折叠结果可以用作trainControl函数的index参数的输入。”

如何通过个人（最好使用插入库）对面板数据进行采样/分区？

2 个答案: