Question

我有一个数据框df

structure(list(x = c(49, 50, 51, 52, 53, 54, 55, 56, 1, 2, 3, 
    4, 5, 14, 15, 16, 17, 163, 164, 165, 153, 154, 72, 38, 39, 40, 
    23, 13, 14, 15, 5, 6, 74, 75, 76, 77, 78, 79, 80, 81, 82, 127, 
    128, 129, 130, 131, 132, 71, 72, 73, 74, 75, 76, 2, 3, 4, 5, 
    6, 99, 100, 101, 10, 11, 3, 30, 50, 51, 52, 53, 54, 56, 64, 66, 
    67, 68, 69, 34, 35, 37, 39, 2, 46, 47, 17, 18, 99, 100, 102, 
    103, 84, 85, 86, 87, 88, 67, 70, 72), y = c(2268.14043972082, 
    2147.62290922552, 2269.1387550775, 2247.31983098201, 1903.39138268307, 
    2174.78291538358, 2359.51909126411, 2488.39004804939, 212.851575751527, 
    461.398994384333, 567.150629704352, 781.775113821961, 918.303706148872, 
    1107.37695799186, 1160.80594193377, 1412.61328924168, 1689.48879626486, 
    685.154353165934, 574.088067465695, 650.30821636616, 494.185166497016, 
    436.312162090908, 641.231373456365, 494.374217984441, 201.745910386788, 
    486.030122926459, 483.045965372879, 265.693628564011, 285.116345260642, 
    291.023782284086, 229.606221692753, 230.952761338012, 1089.06303295676, 
    1255.88808925333, 1087.75402177912, 1068.248897182, 1212.17254891642, 
    884.222588171535, 938.887718005513, 863.582247020735, 1065.91969416523, 
    790.570635510725, 834.500908313203, 710.755041345197, 814.002362551197, 
    726.814950022846, 828.559687148314, 611.564698476112, 603.238720579422, 
    524.322001078981, 565.296378873638, 532.431853589369, 597.174114277044, 
    260.737164468854, 306.72700499362, 283.410379620422, 366.813913489692, 
    387.570173754128, 606.075737104722, 686.408686154056, 705.914347674276, 
    388.602676983443, 477.858510450125, 128.198042456082, 535.519377609133, 
    1893.38468471169, 1819.83262739703, 1827.31409981102, 1640.5816780664, 
    1689.0365549922, 2112.67917439342, 1028.8780498564, 1098.54431357711, 
    1265.26965941035, 1129.58344809909, 820.922447928053, 749.343583476846, 
    779.678206156474, 646.575242339517, 733.953282899613, 461.156280127354, 
    1184.81825619942, 1281.2920902365, 906.813018662913, 798.186995701282, 
    831.365377249207, 764.519073183124, 672.076289062505, 669.879217186302, 
    1265.48484068702, 1193.29000986667, 1156.81486114406, 1199.7373066445, 
    1116.24029749935, 1341.47673353751, 1401.44881976186, 1640.27575962036
    ), ID = 1:97), .Names = c("x", "y", "ID"), row.names = c(NA, 
    -97L), class = "data.frame")

我现在想要根据交叉验证计算一个非线性模型的模型效率，留出一个ID。我实现了这行代码。

library(stats)
library (hydroGOF)

id <- unique(df$ID)
for (i in id){
  fit1 <- try(nls(y~A*x^3+B*x^2+C*x+D, data = df[df$ID != i,], start = list(A=0.02, B=-0.6, C= 50, D=200)), silent=TRUE)
  Out <- if (inherits(fit1, "nls")) NSE(sim = predict(fit1, newdatadata=df[df$ID==i,]), obs = df$y, na.rm=T)
  }

但是，我有此错误消息：

    Error in valindex.default(sim, obs) : 
  Invalid argument: 'length(sim) != length(obs)' !! (96!=97) !!

有人可以帮我解决这个问题吗？

Answer 1

您在上面的代码中有一些小错误和一个很大的逻辑错误，我将在下面解释：

首先，代码应该是这样的：

library(stats)
library (hydroGOF)

id <- unique(df$ID)
for (i in id){
  fit1 <- try(nls(y~A*x^3+B*x^2+C*x+D, data = df[df$ID != i,], start = list(A=0.02, B=-0.6, C= 50, D=200)), silent=TRUE)
  Out <- if (inherits(fit1, "nls")) NSE(sim = predict(fit1, newdata=df[df$ID==i,]), obs = df$y[df$ID==i], na.rm=T)
}

在您的问题中，在NSE函数中，您将参数设置为newdatadata=df[df$ID==i,])而不是newdata=df[df$ID==i,])，即其中有一个额外的data会导致运行时出现问题功能（你拼错了参数:)）。此外，obs参数的长度不正确，因为将使用整个y列，但您只需要df$y[df$ID==i]长度为1（以便与现在的预测相匹配）长度也是一样的。）

现在纠正后，上面的代码将会运行。

但是，运行后，您会看到它会产生警告，指出NSE时您无法使用'sum((obs - mean(obs))^2)=0' => it is not possible to compute 'NSE'。在您的情况下，由于您只有一个障碍，因此计算'sum((obs - mean(obs))^2)=0'将始终为零。

因此，您不能将此技术用于NSE，因为它会因定义而失败（因为您尝试在单个观察中计算NSE）。您应该收集所有留一法的预测，将它们存储在变量中，然后对NSE的变量使用df$y。这将有效。

我的意思是以下（完成了留一个cv）：

Out <- c()
id <- unique(df$ID)
for (i in id){
  fit1 <- try(nls(y~A*x^3+B*x^2+C*x+D, data = df[df$ID != i,], start = list(A=0.02, B=-0.6, C= 50, D=200)), silent=TRUE)
  Out[i] <- if (inherits(fit1, "nls")) sim = predict(fit1, newdata=df[df$ID==i,])
}

现在可以使用：

> NSE(Out, df$y)
[1] 0.3440862

交叉验证中的计算模型效率在R中留下一个主题模式

1 个答案: