如何使 `integrate()` 接受 R 函数中的向量？

Question

我想知道如何让我的函数 Bpp 到 接受一个向量作为它的第一个参数 t?

Bpp = function(t, n1, n2 = NULL){

      N = ifelse(is.null(n2), n1, n1*n2/(n1+n2))
     df = ifelse(is.null(n2), n1 - 1, n1 + n2 - 2)

     H1 = integrate(function(delta)dcauchy(delta, 0, sqrt(2)/2)*dt(t, df, delta*sqrt(N)), -Inf, Inf)[[1]]
     H0 = dt(t, df)
   BF10 = H1/H0
p.value = 2*(1-pt(abs(t), df))

list(BF10 = BF10, p.value = p.value)
}

Bpp(t = -6:6, 20, 20) ## This will give error because `t` is now a vector?

Answer 1

看来我可以在不测试的情况下快速给出答案。在您的 Bpp 中使用以下内容：

# joint density
joint <- function(delta, t) dcauchy(delta, 0, sqrt(2)/2) * dt(t, df, delta*sqrt(N))
# marginal density of `t`
marginal.t <- function (t) integrate(joint, lower = -Inf, upper = Inf, t = t)[[1]]
H1 <- sapply(t, marginal.t)

So, here we also could use Vectorize how would that look like?

使用你原来的 Bpp:

Bpp <- Vectorize(Bpp, vectorize.args = "t")
Bpp(-6:6, 20, 20)

如何使 `integrate()` 接受 R 函数中的向量？

How to make `integrate()` to accept a vector in an R function?

r

function

vectorization

integral

numerical-integration