| Mandel-h | R Documentation | 
Density, distribution function, quantile function and random generation for Mandel's h statistic, a measure of relative deviation from a common mean.
dmandelh(x, g, log = FALSE)
pmandelh(q, g, lower.tail = TRUE, log.p = FALSE)
qmandelh(p, g, lower.tail = TRUE, log.p = FALSE)
rmandelh(B, g)
x, q | 
 vector of quantiles.  | 
p | 
 vector of probabilities.  | 
g | 
 number of means for which h is calculated.  | 
B | 
 Number of observations. If 'length(B) > 1', the length is taken to be the number required.  | 
lower.tail | 
 logical; if TRUE (default), probabilities are P[X <= x]; otherwise, P[X > x].  | 
log, log.p | 
 logical; if TRUE, probabilities p are given as log(p).  | 
Mandel's h is calculated for a particular mean value y[i] in a set of 
mean values y as 
h[i] = ( y[i] - mean(y) )/sd(y) )
The density, probabilities and quantiles can be derived from the beta distribution: (1+h*sqrt(g)/(g-1))/2 is distributed as Beta((g-2)/2, (g-2)/2).
dmandelh returns the density at x, pmandelh the cumulative probability,  
qmandelh the quantiles for probability p and rmandelh returns B 
random values drawn from the distribution. 
Vector values of x, p, q and g are permitted, in which case the functions return vectors.
Note that rmandelh uses B and not n (as do most R random 
number functions) for number of random draws; this is for compatibility with 
the relevant functions for Mandel's k, for which n is conventionally
used for the number of replicates per group. Be careful when using named parameters!
S. L. R. Ellison, s.ellison@lgcgroup.com
None.
pmandelk
	#Generate the 95% and 99% quantiles for comparison with tables in 
	#ISO 5725:1996 Part 2:
	n <- 3:30
	round(qmandelh(0.975, n), 2) #95% 2-tailed
	round(qmandelh(0.995, n), 2) #99% 2-tailed
	
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