R 计算数据帧中特定事件之间的差异

我有三种不同类型的事件(Pass、RHM和REM)，见下面的例子；

现在我想知道根据事件类型的不同，一个特定的传球到另一个偶数的开始时间之间的差异.更具体地说，对于每Pass个人，我想知道现在的Pass人和以前的Pass人，以前的RHM人和以前的REM人之间的区别是什么.

因此，对于第一遍，也就是数据帧中的第二行(Start=668.873)，与前Pass的差异是NaN(因为之前没有)，与前RHM的差异是668.873-668.043=0.83，而与前REM的差异再次是NaN，因为没有.理想情况下，这将导致以下结果；

使其更加复杂的是，DataFrame有两个额外的变量，用于循环上面的变量:Category和Situation；

我已经使用了当前的代码，它适用于1种情况，但它需要重新开始为每种情况.我不知道该怎么做.我在考虑使用dplyr，但不知道如何将其与for循环相结合.

for (i in 1:nrow(x)) {
  
    # PASSES
    # look in rows above the current row and search for last row containing "Pass"
    previousPasses <- which(x$Event[1:i - 1] == "Pass")
    # get last of these passes
    lastPass <- previousPasses[length(previousPasses)]
    # if there are no previous passes, then leave the TimeLastPass column blank
    if (length(lastPass) == 0) {
        x$TimeLastPass[i] <- NaN
    } else {
        # otherwise, fill in the TimeLastPass column with the time of the last pass
        x$TimeLastPass[i] <- round(x$Start[lastPass] - x$Start[i],2)
    }
    
    ### REM
    # look in rows above the current row and search for last row containing "REM"
    previousREMs <- which(x$Event[1:i - 1] == "Referential Eye Movement")
    # get last of these REMs
    lastREM <- previousREMs[length(previousREMs)]
    # if there are no previous REMs, then leave the TimeLastREM column blank
    if (length(lastREM) == 0) {
        x$TimeLastREM[i] <- NaN
    } else {
        # otherwise, fill in the TimeLastREM column with the time of the last REM
        x$TimeLastREM[i] <- round(x$Start[lastREM] - x$Start[i], 2)
    }

    ### RHM
    # look in rows above the current row and search for last row containing "RHM"
    previousRHMs <- which(x$Event[1:i - 1] == "Referential Head Movement")
    # get last of these RHMs
    lastRHM <- previousRHMs[length(previousRHMs)]
    # if there are no previous RHMs, then leave the TimeLastRHM column blank
    if (length(lastRHM) == 0) {
        x$TimeLastRHM[i] <- NaN
    } else {
        # otherwise, fill in the TimeLastRHM column with the time of the last RHM
        x$TimeLastRHM[i] <- round(x$Start[lastRHM] - x$Start[i],2)
    }
}