TSq = (50*60)/(50+60) * (mu1-mu2)' * inv(Sp) * (mu1-mu2);这行代码报错error using ==》mtimes

这个错误通常是因为 `*` 符号左右两边的矩阵/向量维度不匹配，无法进行矩阵乘法运算。请检查一下 `mu1`、`mu2` 和 `Sp` 的维度是否正确。

另外，公式中的 `inv(Sp)` 表示 `Sp` 的逆矩阵，需要保证 `Sp` 可逆。如果 `Sp` 不可逆，使用 `inv()` 函数将会报错。可以使用 `pinv()` 函数来计算广义逆矩阵来避免这个问题。

相关问题

milk.gas = milk[milk$v4 == "gasline",1:3] milk.gas milk.diesel = milk[milk$v4 == "diesel",1:3] milk.diesel n1 = dim(milk.gas)[1] n1 n2 = dim(milk.diesel)[1] n2 p = 3 y.bar.g = colMeans(milk.gas) y.bar.d = colMeans(milk.diesel) s.g = cov(milk.gas) s.d = cov(milk.diesel) s.pl = (s.g*(n1-1)+s.d*(n2-1))/(n1+n2-2) s.pl T.sq = (n1*n2)/(n1+n2)*t(y.bar.g-y.bar.d)%*%solve(s.pl)%*%(y.bar.g-y.bar.d) T.sq cut.off = (n1+n2-2)*p/(n1+n2-p-1)*qf(1-0.01,p,n1+n2-p-1) cut.off把上述R语言代码用自定义函数function表示

可以将上述R语言代码用自定义函数function表示如下：

calculate_Tsq <- function(data) {
  milk.gas <- data[data$v4 == "gasline", 1:3]
  milk.diesel <- data[data$v4 == "diesel", 1:3]
  n1 <- dim(milk.gas)[1]
  n2 <- dim(milk.diesel)[1]
  p <- 3
  y.bar.g <- colMeans(milk.gas)
  y.bar.d <- colMeans(milk.diesel)
  s.g <- cov(milk.gas)
  s.d <- cov(milk.diesel)
  s.pl <- (s.g*(n1-1)+s.d*(n2-1))/(n1+n2-2)
  T.sq <- (n1*n2)/(n1+n2)*t(y.bar.g-y.bar.d)%*%solve(s.pl)%*%(y.bar.g-y.bar.d)
  cut.off <- (n1+n2-2)*p/(n1+n2-p-1)*qf(1-0.01,p,n1+n2-p-1)
  return(list(T.sq=T.sq, cut.off=cut.off))
}

# example usage:
data <- read.csv("milk.csv")
result <- calculate_Tsq(data)
print(result$T.sq)
print(result$cut.off)

pin_memory=True/False

pin_memory参数可以设置为True或False。当pin_memory=True时，数据将被锁页在内存中，这有助于加速数据传输，特别是在使用GPU进行训练时。\[2\]然而，如果计算机的内存不足或系统卡顿，可以将pin_memory设置为False，以释放内存资源。\[1\]因为pin_memory的性能与计算机硬件有关，所以在默认情况下，pytorch将pin_memory设置为False，以适应更广泛的设备。\[3\]
#### 引用[.reference_title]
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