Estimated arginal density of t-statistics from ncpest class
marginal.dt(obj,...)
# S3 method for parncpt
marginal.dt(obj,...)
# S3 method for nparncpt
marginal.dt(obj, ...)
# S3 method for sparncpt
marginal.dt(obj, ...)Other argument passed to dtn.mix, most notably, the approximaiton argument
A function of one argument (x), i.e., the marginal density function.
When obj$data$df are all equal to each other, a single marginal density is clearly defined for all obj$data$tstat. Otherwise,
the marginal density is defined as a discrete mixture of densities, one for each distinct degree of freedom,
with mixing proportion based on that of obj$data$df.
Qu L, Nettleton D, Dekkers JCM. (2012) Improved Estimation of the Noncentrality Parameter Distribution from a Large Number of $t$-statistics, with Applications to False Discovery Rate Estimation in Microarray Data Analysis. Biometrics, 68, 1178--1187.