q_gg: Outlier Probability Under GG Assumption (Using Joint Method)

In matthew-seth-smith/replicateOutliers: Outlier Detection Methods for Replicated Data

Description

This function provides the outlier probability of a pair of replicates described by (Delta=d, Zeta=z) using the joint method assuming the underlying data X_1 and X_2 follow independent (and possibly identically distributed) GG distributions. We use the parameterization used by the R package flexsurv, given by Kotz and Johnson (1970). We numerically integrate the PDF given by the function f_gg using the function adaptIntegrate in the package cubature.

Usage

q_gg(d, z, alpha_1, beta_1, c_1, alpha_2, beta_2, c_2)

Arguments

d	The absolute difference between two replicates
z	The coefficient of variation (CV) between two replicates
alpha_1	The parameter alpha > 0 in the GG distribution for X_1
beta_1	The parameter beta > 0 in the GG distribution for X_1
c_1	The parameter c > 0 in the GG distribution for X_1
alpha_2	The parameter alpha > 0 in the GG distribution for X_2
beta_2	The parameter beta > 0 in the GG distribution for X_2
c_2	The parameter c > 0 in the GG distribution for X_2

Value

The joint probability of observing Delta <= d and Z >= z (if d < 0) or Delta >= d and Z >= z (if d >= 0)

matthew-seth-smith/replicateOutliers documentation built on Jan. 24, 2020, 9:34 p.m.