GaussianNoise: Gaussian Noise

In juancbellass/time-series-r-package: Time Series Similarity Indices

Gaussian Noise

Description

Generates a vector _ts.normal_ is created where every element of _ts.normal_ follow a N(mu, sigma2) distribution. The _prop_ selected randomly. The _prop_ randomly. If Y_i_ is selected then it is replaced by _Y_i_ + _ts.normal_i_. This procedure is called additive contamination of _prob_

Usage

GaussianNoise(y, prob, mu, sigma)

Arguments

prob	The probability of success of the binomial distribution. A number between 0 and 1.
mu	The mean of the normal distribution.
sigma	The standard deviation of the normal distribution. A real number.
Y	The time-series (as numeric) to be contaminated.

Value

The y matrix with additive noise.

juancbellass/time-series-r-package documentation built on Aug. 26, 2023, 8:06 p.m.