Hmean(x, method = c("classic", "boot"), conf.level = NA, sides = c("two.sided","left","right"), na.rm = FALSE, ...)
"classic"
, "boot"
.
See boot.ci
.NA
."two.sided"
(default), "left"
or "right"
. You can specify just the initial letter. "left"
would be analogue to a hypothesis of "greater"
in a t.test
.NA
values should be stripped before the computation proceeds. Defaults to FALSE
.boot
function. Supported arguments are type
("norm"
, "basic"
, "stud"
, "perc"
, "bca"
), parallel
and the number of bootstrap replicates R
. If not defined those will be set to their defaults, being "basic"
for type
, option "boot.parallel"
(and if that is not set, "no"
) for parallel
and 999
for R
.
To compute the harmonic mean, 1/x
is first calculated, before the arithmetic mean and its confidence interval are computed by MeanCI
. The harmonic mean is then the reciprocal of the arithmetic mean of the reciprocals of the values. The same applies to the confidence interval.
The harmonic mean is restricted to strictly positive inputs, if any argument is negative, then the result will be NA
.
If the lower bound of the confidence interval is not greater than zero, then the confidence interval is not defined, and thus NA
will be reported.
Use sapply
to calculate the measures from data frame, resp. from a matrix.
Gmean
x <- runif(5)
Hmean(x)
m <- matrix(runif(50), nrow = 10)
apply(m, 2, Hmean)
sapply(as.data.frame(m), Hmean)
Run the code above in your browser using DataLab