Confuse-a-Cat [General Sta­tis­tics]

posted by Helmut Homepage – Vienna, Austria, 2020-06-30 11:33 (292 d 02:06 ago) – Posting: # 21614
Views: 2,978

Hi ElMaestro,

» OK, I try again.

THX for your patience.

» I give you two functions of a sample x, call the functions f and g (or Z and s, or alpha and beta, or apple and banana). Symbols not important. How do we determine that f and g are independent?

[image] Feel like a cat.

In the OP (and now?) you were talking about a test and whether the numerator and denominator constructing it are independent functions of \(x\).$$t=\frac{Z}{s},\; Z=f(x)\:\wedge\:s=g(x)$$Somehow I have the feeling that the discussion moves towards transformations. Another cup of tea.

x    <- seq(1, 2, length.out = 100)
fun  <- data.frame(f.1 = sin(x), f.2 = sin(x+1), f.3 = cos(x),
                   f.4 = x^2,    f.5 = sqrt(x),  f.6 = tan(x))
corr <- data.frame(f.1 = rep(NA, 6), f.2 = NA, f.3 = NA,
                   f.4 = NA, f.5 = NA, f.6 = NA)
colnames(corr) <- rownames(corr) <- c("sin(x)", "sin(x+1)", "cos(x)",
                                      "x^2", "sqrt(x)", "tan(x)")
for (j in 1:nrow(corr)) {
  for (k in 1:ncol(corr)) {
    if (k < j) {
      corr[k, j] <- sprintf("%+7.5f", cor(fun[, j], fun[, k]))
    }
  }
}
corr[is.na(corr)] <- ""
corr[-nrow(corr), ]


» […] how about generally, when f and g are not necessarily mean and dispersion indicators of the x-sample from a normal distribution?

Are you not happy with existing tests (questioning the independence) and are trying to develop a new one? How does the “perturbation on the data” come into play?
Slowly I get the feeling that I can’t follow your arguments and I’m not qualified to answer your question. Sorry.

Dif-tor heh smusma 🖖
Helmut Schütz
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