Calculates the Normalized Absolute Deviation between the empirical moments and the moments of the provided distribution. Corresponds to the Kolmogorov-Smirnov test statistic for the zeroth moment.
nmad_test( x, r =0, dist, prior =1, coeff, stat = c("NULL","max","sum"),...)
Arguments
x: data vector
r: moment parameter
dist: character vector containing distribution
prior: named list of priors, defaults to 1
coeff: named list of coefficients
stat: character vector indicating which statistic should be calculated: none (NULL), the maximum deviation "max" or the sum of deviations "sum". Defaults to NULL.
...: Additional arguments can be passed to the parametric moment call.
Examples
x <- rlnorm(1e2, meanlog =-0.5, sdlog =0.5)nmad_test(x = x, r =0, dist ="lnorm", coeff = c(meanlog =-0.5, sdlog =0.5))nmad_test(x = x, r =0, dist ="lnorm", coeff = c(meanlog =-0.5, sdlog =0.5), stat ="max")nmad_test(x = x, r =0, dist ="lnorm", coeff = c(meanlog =-0.5, sdlog =0.5), stat ="sum")