g_: Estimator using the exponential distribution.

In softloud/varameta: Estimators for the Variance of the Sample Median

Estimator using the exponential distribution.

Description

These estimators are for comparison purposes with the estimator proposed.

Usage

g_exp(n, m)

g_norm(n, m, spread, spread_type = "iqr")

g_lnorm(n, m, spread, spread_type = "iqr")

g_cauchy(n, m, spread, spread_type = "iqr")

Arguments

n	sample size
m	Sample median.
spread	Interquartile range or range value.
spread_type	"iqr" or "range", defaults to "iqr".

Details

This estimator assumes we have observed a m, m, and sample size n. We naively assume an exponential distribution \sim exp(λ), so that the m ν := log(2)/λ.

This function then estimates λ := log(2) / m and approximates the standard error of the sample (2 √{n} g(m; λ = log(2) / m))^{-1} where g is the exponential density.

See Also

Other one_neet Inputs and outputs neet tested.: bland, effect_se(), hozo, wan_c1, wan_c2

softloud/varameta documentation built on Feb. 8, 2023, 12:12 a.m.