Nested generalized means

Calculate a weighted (outer) generalized mean of two (inner) generalized means (i.e., crossing means).

Usage

nested_gmean(
  x,
  weights = list(NULL, NULL),
  order = c(1, -1),
  outer_weights = NULL,
  outer_order = 0,
  na.rm = FALSE
)

Arguments

x

[numeric > 0] A strictly positive numeric vector.

weights

[list] A list of positive numeric vector of weights, each the same length as x, for both of the inner generalized means. NULL elements of weights equally weight each element of x. The default uses equal weights for both inner generalized mean.

order

[numeric(2)] A finite numeric vector giving the order of each of the inner generalized means. The default computes an arithmetic mean and a harmonic mean.

outer_weights

[numeric(2)] A strictly positive numeric vector weights for each of the inner generalized means as used in the outer generalized mean. The default weights each inner generalized mean equally.

outer_order

[numeric(1)] A finite number giving the order of the outer generalized mean. The default uses a geometric mean.

na.rm

[logical(1)] Should missing values in x and weights be removed? By default missing values are not removed. Note that removal of missing values is balanced across x and both elements of weights.

Value

A numeric value for the nested generalized mean.

See also

Other math functions: emean(), gmean(), scale_weights(), transmute_weights(), transmute_weights2(), update_weights()

Examples

x <- 1:3
w1 <- c(0.25, 0.25, 0.5)
w2 <- c(0.3, 0.3, 0.4)
# Calculate the geometric mean of the arithmetic and harmonic means
# to make a Fisher index.
nested_gmean(x, list(w1, w2))
#> [1] 1.963961