diid.disturbance: Construct feasible Random Noise Generating a Bernoulli...

In spgs: Statistical Patterns in Genomic Sequences

Construct feasible Random Noise Generating a Bernoulli Process

Description

Produces a sequence of random noise which would generate an observed sequence of finite symbols provided that the sequence of symbols results from a Bernoulli process.

Usage

diid.disturbance(x, random = TRUE,  estimates = FALSE)

Arguments

x	A sequence of finite symbols represented as a character vector.
random	This can be a logical value or a number in the range 0-1. If ‘⁠TRUE⁠’, random noise will be generated. If ‘⁠FALSE⁠’, the constant value 0.5 will be used as the noise source. If a value in the range 0-1 is specified, that value will be used as a constant noise source. the default value is ‘⁠TRUE⁠’.
estimates	A logical value specifying if the distribution estimated for the Bernoulli process should be included in the return.

Value

If ‘⁠estimates⁠’ is ‘⁠TRUE⁠’, returns a list containing the following components:

disturbance	the sequence of random noise as a numeric vector.
stat.dist	The stationary distribution estimated from x.

Otherwise, if ‘⁠estimate⁠’ is ‘⁠FALSE⁠’, returns the sequence of random noise as a numeric vector.

Author(s)

Andrew Hart and Servet Martínez

See Also

markov.test, diid.test, markov.disturbance

spgs documentation built on Oct. 3, 2023, 5:07 p.m.