derivMOP: Derivative of a MOP

In MoTBFs: Learning Hybrid Bayesian Networks using Mixtures of Truncated Basis Functions

Derivative of a MOP

Description

Compute the derivative of an "motbf" object with 'mop' subclass.

Usage

derivMOP(fx)

Arguments

fx	An "motbf" object of the 'mop' subclass.

Value

The derivative which is also an "motbf" function.

See Also

univMoTBF for learning and derivMoTBF for general "motbf" models.

Examples

## 1. EXAMPLE
X <- rexp(1000)
Px <- univMoTBF(X, POTENTIAL_TYPE="MOP")
derivMOP(Px)

## 2. EXAMPLE
X <- rnorm(1000)
Px <- univMoTBF(X, POTENTIAL_TYPE="MOP")
derivMOP(Px)

## Not run: 
## 3. EXAMPLE
X <- rnorm(1000)
Px <- univMoTBF(X, POTENTIAL_TYPE="MTE")
derivMOP(Px)
## Error in derivMOP(Px): fx is an 'motbf' function but not 'mop' subclass.
class(Px)
subclass(Px)

## End(Not run)

MoTBFs documentation built on April 18, 2022, 5:06 p.m.