【发布时间】:2018-12-20 02:38:18
【问题描述】:
我想知道,为什么当我直接提供 q 的值时(见 f2),uniroot() 工作得非常好,但是当我提供 q作为其他输入值的函数uniroot()(参见f1)失败?
在代码中,所有带有...1 后缀(例如f1)的内容都与我间接提供q 的时间有关。并且所有带有...2 后缀(例如f2)的东西都与我直接提供q 时有关。
我的目标是求解df2 使得y = .15(正确答案是~ 336.3956)。 (请运行下面的整个代码。)
alpha = c(.025, .975); df1 = 3; q = 48.05649 ; peta = .3 # input values
f1 <- function(alpha, q, df1, df2, ncp){ # Objective function (`q` indirectly)
alpha - suppressWarnings(pf(q = (peta / df1) / ((1 - peta)/df2), df1, df2,
ncp, lower.tail = FALSE))
}
f2 <- function(alpha, q, df1, df2, ncp){ # Objective function (`q` directly)
alpha - suppressWarnings(pf(q = q, df1, df2, ncp, lower.tail = FALSE))
}
ncp1 <- function(df2){ # root finding
b <- sapply(c(alpha[1], alpha[2]),
function(x) uniroot(f1, c(0, 1e7), alpha = x, q = peta, df1 = df1, df2 = df2)[[1]])
b / (b + (df2 + 4))
}
ncp2 <- function(df2){ # root finding
b <- sapply(c(alpha[1], alpha[2]),
function(x) uniroot(f2, c(0, 1e7), alpha = x, q = q, df1 = df1, df2 = df2)[[1]])
b / (b + (df2 + 4))
}
m1 <- function(df2, y){ # A Utility function
abs(abs(diff(ncp1(df2))) - y)
}
m2 <- function(df2, y){ # A Utility function
abs(abs(diff(ncp2(df2))) - y)
}
optimize(m1, c(1, 1e7), y = .15)[[1]] # Incorrect answer: 1e+07
optimize(m2, c(1, 1e7), y = .15)[[1]] # Correct answer: 336.3956
【问题讨论】:
标签: r function math optimization linear-algebra