Question

我有一个数据框，我正在使用for循环运行蒙特卡罗模拟，以生成模拟分布。当我测试模拟代码时，我只是访问数据框中的第一个观察点：

Male.MC <-c()
for (j in 1:100){
    for (i in 1:1)  {
        # u2 <- Male.DistF$Male.stddev_u2[i] * rnorm(1, mean = 0, sd = 1)
        u2 <- Male.DistF$RndmEffct[i] * rnorm(1, mean = 0, sd = 1)
        mc_bca <- Male.DistF$lmefits[i] + u2
        temp <- Lambda.Value*mc_bca+1
        ginv_a <- temp^(1/Lambda.Value)
        d2ginv_a <- max(0,(1-Lambda.Value)*temp^(1/Lambda.Value-2))
        mc_amount <- ginv_a + d2ginv_a * Male.DistF$Male.var[i]^2 / 2
        z <- c(RespondentID <- Male.DistF$RespondentID[i], 
                   Male.DistF$AgeFactor[i], Male.DistF$SampleWeight[i], 
        Male.DistF$Male.var[i], Male.DistF$lmefits[i], u2, mc_amount) 
        Male.MC <- as.data.frame(rbind(Male.MC,z))
    }
}
colnames(Male.MC) <- c("RespondentID", "AgeFactor", 
                       "SampleWeight", "VarByAge", 
                       "lmefits", "u2", "mc_amount")

代码工作得很漂亮，除了Male.DistF$RespondentID是一个因素，我没有得到因子水平输出，而是得到因子索引，在这种情况下我得到1作为{{1在RespondentID数据框中按升序排列。我对Male.DistF有同样的问题，我得到索引而不是因子级别。

AgeFactor

如何使`Male.MC1数据框包含这两个变量的因子水平？我试过了：

head(Male.MC)
  RespondentID AgeFactor SampleWeight  VarByAge  lmefits         u2 mc_amount
z            1         3    0.4952835 0.4189871 15.22634  0.2334501 11582.681
2            1         3    0.4952835 0.4189871 15.22634  0.3205741 11984.220
3            1         3    0.4952835 0.4189871 15.22634 -0.5674165  8420.678
4            1         3    0.4952835 0.4189871 15.22634 -0.5426489  8505.421
5            1         3    0.4952835 0.4189871 15.22634  0.4878695 12790.565
6            1         3    0.4952835 0.4189871 15.22634  0.1556925 11234.583

和

z <- c(RespondentID <- as.character(Male.DistF$RespondentID[i]), 
       Male.DistF$AgeFactor[i], Male.DistF$SampleWeight[i], 
       Male.DistF$Male.var[i], Male.DistF$lmefits[i], u2, mc_amount)

修复z <- c((as.character(Male.DistF$RespondentID[i])), Male.DistF$AgeFactor[i], Male.DistF$SampleWeight[i], Male.DistF$Male.var[i], Male.DistF$lmefits[i], u2, mc_amount)输出，但是我对该语法做错了，并且它试图将所有输出转换为因子：

RespondentID

对于测试，这是输入数据框There were 50 or more warnings (use warnings() to see the first 50) str(Male.MC) 'data.frame': 100 obs. of 7 variables: $ RespondentID: Factor w/ 1 level "100020": 1 1 1 1 1 1 1 1 1 1 ... ..- attr(*, "names")= chr "z" "" "" "" ... $ AgeFactor : Factor w/ 1 level "3": 1 1 1 1 1 1 1 1 1 1 ... ..- attr(*, "names")= chr "z" "" "" "" ... $ SampleWeight: Factor w/ 1 level "0.495283471": 1 1 1 1 1 1 1 1 1 1 ... ..- attr(*, "names")= chr "z" "" "" "" ... $ VarByAge : Factor w/ 1 level "0.418987052181831": 1 1 1 1 1 1 1 1 1 1 ... ..- attr(*, "names")= chr "z" "" "" "" ... $ lmefits : Factor w/ 1 level "15.2263403968895": 1 1 1 1 1 1 1 1 1 1 ... ..- attr(*, "names")= chr "z" "" "" "" ... $ u2 : Factor w/ 1 level "-0.100954008424162": 1 NA NA NA NA NA NA NA NA NA ... ..- attr(*, "names")= chr "z" "" "" "" ... $ mc_amount : Factor w/ 1 level "10151.4582133747": 1 NA NA NA NA NA NA NA NA NA ... ..- attr(*, "names")= chr "z" "" "" "" ...的前几行：

Male.DistF

AgeFactor RespondentID SampleWeight IntakeAmt RndmEffct NutrientID Gender Age BodyWeight IntakeDay BoxCoxXY lmefits lmeres TotWts GrpWts NumSubjects TotSubjects Male.var 1725 9to13 100020 0.4952835 12145.852 0.30288536 267 1 12 51.6 Day1Intake 15.61196 15.22634 0.27138449 2291.827 763.0604 525 2249 0.4189871 203 14to18 100419 0.3632839 9591.953 0.02703093 267 1 14 46.3 Day1Intake 15.01444 15.31373 -0.18039624 2291.827 472.3106 561 2249 0.3365423是Lambda.Value。 0.1上的信息是：

Male.DistF

从我的str(Male.DistF) 'data.frame': 2249 obs. of 18 variables: $ AgeFactor : Ord.factor w/ 4 levels "1to3"<"4to8"<..: 3 4 3 4 2 2 3 1 1 3 ... $ RespondentID: Factor w/ 2249 levels "100020","100419",..: 1 2 3 4 5 6 7 8 9 10 ... $ SampleWeight: num 0.495 0.363 0.495 1.326 2.12 ... $ IntakeAmt : num 12146 9592 7839 11113 7150 ... $ RndmEffct : num 0.3029 0.027 0.0772 0.4667 -0.1593 ... $ NutrientID : int 267 267 267 267 267 267 267 267 267 267 ... $ Gender : int 1 1 1 1 1 1 1 1 1 1 ... $ Age : int 12 14 11 15 6 5 10 2 2 9 ... $ BodyWeight : num 51.6 46.3 46.1 63.2 28.4 18 38.2 14.4 14.6 32.1 ... $ IntakeDay : Factor w/ 2 levels "Day1Intake","Day2Intake": 1 1 1 1 1 1 1 1 1 1 ... $ BoxCoxXY : num 15.6 15 14.5 15.4 14.3 ... $ lmefits : num 15.2 15.3 15 15.8 14.3 ... $ lmeres : num 0.271 -0.18 -0.342 -0.424 -0.053 ... $ TotWts : num 2292 2292 2292 2292 2292 ... $ GrpWts : num 763 472 763 472 779 ... $ NumSubjects : int 525 561 525 561 613 613 525 550 550 525 ... $ TotSubjects : int 2249 2249 2249 2249 2249 2249 2249 2249 2249 2249 ... $ Male.var : num 0.419 0.337 0.419 0.337 0.267 ...数据中可以看出，对于第一次观察的100次重复，在Male.DistF数据框中，我希望Male.MC为100020（而不是RespondentID）和1作为9to13（而不是AgeFactor）。我的输出指令出了什么问题，如何解决这个问题？特别是，我不理解为什么我使用3的尝试误入歧途影响整个输出。另外，我也欢迎加快循环的建议。我所做的就是在as.character数据框中为每个观察值构建100组值。

Answer 1

您可以尝试替换

行

z <- c(...

将新行创建为向量，即，强制所有元素具有相同的类型，使用1行data.frame，以保持列的类型。

z <- data.frame(
  RespondentID = Male.DistF$RespondentID[i], 
  AgeFactor    = Male.DistF$AgeFactor[i], 
  SampleWeight = Male.DistF$SampleWeight[i], 
  VarByAge     = Male.DistF$Male.var[i], 
  lmefits      = Male.DistF$lmefits[i], 
  u2           = u2, 
  mc_amount    = mc_amount
)

R：如何从for循环而不是索引输出因子级别？

1 个答案: