我有一个数据集，我正在尝试使用插入符号包中的timeslice参数对滚动预测源进行线性回归和交叉验证。
model_data <- structure(list(date = structure(c(17536, 17543, 17550, 17557,
17564, 17571, 17578, 17585, 17592, 17599, 17606, 17613, 17627,
17634, 17641, 17648, 17655, 17662, 17669, 17676), class = "Date"),
X_VIX = c(2.2213750375685, 2.31845844215034, 2.42214432805168,
2.40514168131914, 2.85128431141804, 3.36936262373057, 2.9683610253704,
2.80275413657151, 2.97501923195645, 2.68375750853317, 2.76000994003292,
3.2136622980244, 3.06758771065442, 2.8570447537801, 2.8261294299261,
2.73501664933202, 2.69259809654329, 2.53765721517353, 2.59674613154354,
2.58173083442354), SPY = c(5.60701205088108, 5.62333630310206,
5.63225572417907, 5.65402063155967, 5.61440913588427, 5.56243719680005,
5.60587746051261, 5.61171885108039, 5.59101157722328, 5.62674867567328,
5.61385781089189, 5.55315331809212, 5.55960413149059, 5.58029568095444,
5.58578686015654, 5.58559935147548, 5.58357145257487, 5.60892221562235,
5.60333574433455, 5.60635336283354), bamlc0a2caa = c(-0.59783700075562,
-0.63487827243597, -0.616186139423817, -0.63487827243597,
-0.673344553263766, -0.579818495252942, -0.527632742082372,
-0.510825623765991, -0.446287102628419, -0.430782916092454,
-0.385662480811985, -0.328504066972036, -0.342490308946776,
-0.385662480811985, -0.415515443961666, -0.400477566597125,
-0.371063681390832, -0.400477566597125, -0.415515443961666,
-0.400477566597125)), .Names = c("date", "X_VIX", "SPY",
"bamlc0a2caa"), row.names = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L,
9L, 10L, 11L, 12L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L), class = "data.frame")
myTimeControl <- trainControl(method='timeslice',
initialWindow = 5,
horizon = 1,
fixedWindow = FALSE)
lm.mod <- train(bamlc0a2caa ~ . -date,
data = model_data, method = 'lm',
trControl = myTimeControl, metric='Rsquared')
lm.mod
列车功能始终返回与NA R平方值相同的错误。我的代码中没有NA值，n＆gt; p参数。我是新的插入包，所以非常感谢任何帮助解决问题。谢谢！
Something is wrong; all the Rsquared metric values are missing:
RMSE Rsquared MAE
Min. :0.04848 Min. : NA Min. :0.04848
1st Qu.:0.04848 1st Qu.: NA 1st Qu.:0.04848
Median :0.04848 Median : NA Median :0.04848
Mean :0.04848 Mean :NaN Mean :0.04848
3rd Qu.:0.04848 3rd Qu.: NA 3rd Qu.:0.04848
Max. :0.04848 Max. : NA Max. :0.04848
NA's :1
Error: Stopping
In addition: Warning message:
In nominalTrainWorkflow(x = x, y = y, wts = weights, info = trainInfo, :
There were missing values in resampled performance measures.