multiply.norm: Linear Transformations

In vincenzocoia/distplyr: Manipulation of Univariate Distributions

Linear Transformations

Description

shift() a distribution by adding a constant, or multiply() a distribution by a constant. flip() is a specific case of multiplying a distribution by -1, resulting in "flipping" the distribution about 0.

Usage

multiply.norm(distribution, constant)

Arguments

distribution	A probability distribution.
constant	A single numeric by which to shift or multiply the distribution by.

Details

Specifically, if X is a random variable coming from a distribution, then the resulting distributions are as follows:

• For shift(), is the distribution of X + constant.

• For multiply(), is the distribution of X * constant.

• For flip(), is the distribution of -X.

Although the multiply() function accepts negative constants, the corresponding "scale" distribution class only holds positive constants, delegating a potential negative sign to the "flip" class.

Value

A distribution, shifted or multiplied by the constant. Specifically, a distribution with subclass "shift", "scale", or "flip".

Note

You can also use the binary operations +, -, *, and / to access these transformations.

See Also

invert()

Examples

d_pois <- distionary::dst_pois(1.1)
d_norm <- distionary::dst_norm(4, 1)
d_unif <- distionary::dst_unif(0, 1)

# Shift a Poisson distribution by 1.
shift(d_pois, 1)
d_pois + 1

# Multiply a Uniform distribution by 2.
multiply(d_unif, 2)
d_unif * 2

# Flip a Normal distribution.
flip(d_norm)
-d_norm

# Combine multiple operations:
4 - 2 * d_pois

vincenzocoia/distplyr documentation built on March 5, 2024, 9:45 p.m.