conf.limits.ncf: Confidence limits for noncentral F parameters

Description

Function to determine the noncentral parameter that leads to the observed F-value, so that a confidence interval around the population F-value can be conducted. Used for forming confidence intervals around noncentral parameters (given the monotonic relationship between the F-value and the noncentral value).

Usage

conf.limits.ncf(F.value = NULL, conf.level = .95, df.1 = NULL, 
df.2 = NULL, alpha.lower = NULL, alpha.upper = NULL, tol = 1e-09,
Jumping.Prop = 0.1)

Arguments

F.value

the observed F-value

conf.level

the desired degree of confidence for the interval

df.1

the numerator degrees of freedom

df.2

the denominator degrees of freedom

alpha.lower

Type I error for the lower confidence limit

alpha.upper

Type I error for the upper confidence limit

tol

tolerance for iterative convergence

Jumping.Prop

Value used in the iterative scheme to determine the noncentral parameters necessary for confidence interval construction using noncentral F-distributions (0 < Jumping.Prop < 1) (users should not need to change this value)

Value

Details

This function is the relied upon by the ci.R2 and ss.aipe.R2. If the function fails (or if a function relying upon this function fails), adjust the Jumping.Prop (to a smaller value).

Examples

Run this code

conf.limits.ncf(F.value = 5, conf.level = .95, df.1 = 5, 
df.2 = 100)

# A one sided confidence interval.
conf.limits.ncf(F.value = 5, conf.level = NULL, df.1 = 5, 
df.2 = 100, alpha.lower = .05, alpha.upper = 0, tol = 1e-09,
Jumping.Prop = 0.1)