calculateNbcf: calculateNbcf

In kojikoji/nbcf: Change point detection for time course multi negative binomial observation

Description

Function for detecting change points and changed variates

Usage

calculateNbcf(count.mat, t.vec, mean.bias.vec, alpha = 1, beta = 1,
  r = 30, lambda = 0.01, p.res = 1000, count.res = 1000,
  t.res = 100, map.fix.num = NULL, method = "nbinom",
  calc.bf.list = TRUE)

Arguments

count.mat	dgCmatrix, Count matrix. Each row represent each variate. Each column represent each observation
t.vec	Numeric vector, Observation time
mean.bias.vec	Numeric vector, Relative mean bias for each observation
r	Numeric, Size parameters of negative binomial distribution.
lambda	Numeric, Prior probability the change point occur each step
p.res	Integer, Approximation resolution of parameter p
count.res	Integer, Approximation resolution of count.
t.res	Integer, Approximation resolution of t.
map.fix.num	Integer, the number of map change points. If it is NULL, the point number is automaticaly estimated
method	Character, this calculate least variance break points when you specify this as "variance"

Details

This function is responsible for main calculation of this package. This calculate simulated change points and MAP estimates of them, and detect variates which significantly changed between each MAP estimated change points.

Value

Nbcf, nbcf Instance of class Nbcf

Author(s)

Yasuhiro Kojima

See Also

[Nbcf]

kojikoji/nbcf documentation built on June 16, 2019, 6:08 p.m.