我有两年来的每日地理空间数据。数据在两个nc文件中，每个文件包含365天的数据。我想对数据进行计算，然后计算每个网格中每年12个月的月平均值。

lons <- 584
lats <- 712
MyValues_ym <- array(0., c(lons, lats, 2, 12))
MyCalculation <- array(0., c(lons, lats, ts))  ## set up data array to fit dailycalculations 
MyMonths = c('01','02','03','04','05','06','07','08','09','10','11','12')
ts <- dim(P)[[3]]  ## set MyCalculation array coordinates the same as precipitation coordinates
## Dimension of precipitation coordinates: [584L, 712L, 365L]

## calculate MeanMonthly  #calculated monthly q0 
## Loop over months
for (m in 1:12) {
  MyValues_ym[, , y - 1982, m] <- apply(MyCalculation, c(2), mean)
}

这就是错误：

Error in `[<-`(`*tmp*`, , , y - 1982, m, value = c(NA_real_, NA_real_,  : 
  subscript out of bounds

任何帮助将不胜感激。
我尝试过使用rowMeans，但这并不是计算数组时间维度的平均值。我不知道如何计算所需特定尺寸的平均值。
我用RowMeans试了一下：

# Loop over months
    for (m in 1:12) {     
    my_months_yearly <- format(daterange, '%m') == MyMonths[m]    
    MyValues_ym[,,y-1982,m]=rowMeans(Q0d[,,my_months_yearly], na.rm = TRUE, dims = 2)

编辑

我现在做了一个MRE：

lons <- 10
lats <- 10

MyYearlyMonthlyData <- array(0., c(lons,lats,1,12)) ## set up array for monthly calculation 
MyCalculationYr1 <- array(runif(1:100), c(lons, lats, 365)) ## set up data array to fit dailycalculations 

## set up the date range and months for the loop
start = '1985-01-01'
end = '1985-12-31'
daterange = seq(as.Date(start), as.Date(end), "days")
MyMonths = c('01','02','03','04','05','06','07','08','09','10','11','12')
y=1985

## the loop to generate monthly values of each day of each month for the year

for (m in 1:12) { 
  blMM <- format(daterange,'%m') == MyMonths[m]
  MyYearlyMonthlyData[,,y-1984,m] = rowMeans(MyCalculationYr1[,,blMM],na.rm=TRUE,dims=2) 
}