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我有一个数据框，我正在运行蒙特卡罗模拟，使用 for 循环来生成模拟分布。当我测试模拟代码时，我只是在访问数据框中的第一个观察结果：

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")

代码工作得很好，除了这Male.DistF$RespondentID是一个因素，我没有得到因素级别的输出，而是得到因素索引，在这种情况下，我得到1了因为RespondentIDs 在Male.DistF数据框中按升序排列。我有同样的问题AgeFactor，我得到的是指数而不是因子水平。

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

如何使`Male.MC1 数据框包含这两个变量的因子水平？我试过了：

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)

和

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)

修复RespondentID输出，但我对该语法做错了，它试图将所有输出转换为因子：

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" "" "" "" ...

为了测试，这里是输入数据框的前几行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

Lambda.Value是0.1。上的资料Male.DistF是：

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 ...

正如您从我的Male.DistF数据中看到的那样，对于第一次观察的 100 次重复，在Male.MC数据框中，我希望100020作为RespondentID(and not 1) 和9to13( AgeFactorand not 3)。我的输出指令哪里出错了，我该如何解决？特别是，我没有理解为什么我的使用尝试as.character如此严重地误入歧途，以至于影响了整个输出。顺便说一句，我也欢迎加快循环速度的建议。我所做的只是为我的Male.DistF数据框中的每个观察值构建 100 组值。

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1 回答 1

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您可以尝试替换该行

z <- c(...

它将新行创建为向量，即强制所有元素具有相同的类型，具有 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
)
于 2012-01-08T02:53:00.790 回答