marg_pow: Marginal log-likelihood and posterior density of discrete...

In clement-lee/rackage: Network Analysis of Dependencies of CRAN Packages

Marginal log-likelihood and posterior density of discrete power law via numerical integration

Description

Marginal log-likelihood and posterior density of discrete power law via numerical integration

Usage

marg_pow(df, lower, upper, m_alpha, s_alpha, by = 0.001)

Arguments

df	A data frame with at least two columns, x & count
lower	Real number greater than 1, lower limit for numerical integration
upper	Real number greater than lower, upper limit for numerical integration
m_alpha	Real number, mean of the prior normal distribution for alpha
s_alpha	Positive real number, standard deviation of the prior normal distribution for alpha
by	Positive real number, the width of subintervals between lower and upper, for numerical integration and posterior density evaluation

Value

A list: log_marginal is the marginal log-likelihood, posterior is a data frame of non-zero posterior densities

clement-lee/rackage documentation built on March 28, 2024, 7:05 p.m.