conf.limits.nc.chisq {MBESS}

Confidence limits for noncentral chi square parameters

Description

Function to determine the noncentral parameter that leads to the observed Chi.Square-value, so that a confidence interval for the population noncentral chi-squrae value can be formed.

Usage

conf.limits.nc.chisq(Chi.Square=NULL, conf.level=.95, df=NULL, 
alpha.lower=NULL, alpha.upper=NULL, tol=1e-9, Jumping.Prop=.10)

Arguments

Chi.Square

the observed chi-square value

conf.level

the desired degree of confidence for the interval

df

the 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 chi square-distributions (0 < Jumping.Prop < 1)

Details

If the function fails (or if a function relying upon this function fails), adjust the Jumping.Prop (to a smaller value).

Value

Lower.Limit

Value of the distribution with Lower.Limit noncentral value that has at its specified quantile Chi.Square

Prob.Less.Lower

Proportion of cases falling below Lower.Limit

Upper.Limit

Value of the distribution with Upper.Limit noncentral value that has at its specified quantile Chi.Square

Prob.Greater.Upper

Proportion of cases falling above Upper.Limit

Author(s)

Ken Kelley (University of Notre Dame; [e-mail]); Keke Lai (University of California–Merced)

See Also

conf.limits.nct, conf.limits.ncf

Examples

# A typical call to the function.
conf.limits.nc.chisq(Chi.Square=30, conf.level=.95, df=15)

# A one sided (upper) confidence interval.
 conf.limits.nc.chisq(Chi.Square=30, alpha.lower=0, alpha.upper=.05, 
 conf.level=NULL, df=15)