MoTBFs (version 1.2)

newRangePriorData: Redefining the Domain

Description

Computes the new domain of two datasets.

Usage

newRangePriorData(fPI, priorData, N, domain, s, POTENTIAL_TYPE)

Arguments

fPI

The fitted function to the prior data of class "motbf".

priorData

A "numeric" array with the values we want to include as prior information.

N

A "numeric" value which is the size of the data.

domain

A "numeric" array with the limits where defining the data function.

s

A "numeric" value which is the confident of the expert in his information. It is between 0 and the data size.

POTENTIAL_TYPE

A "character" string giving the potential of the model, i.e. "MOP" if the basis functions are polynomials, or "MTE" if they are exponentials.

Value

A "numeric" array which contains the new domain of the prior function.

Examples

# NOT RUN {
## Data
X <- rnorm(15)

## Prior Data
priordata <- rnorm(5000)

## Learning
type = "MTE" 
fPrior <- univMoTBF(priordata, POTENTIAL_TYPE = type)

## New range
confident <- 5 ## confident <- 1,2,...,length(X)
domain <- range(X)
N <- length(X)
newRange <- newRangePriorData(fPrior, priorData = priordata, N = N,
domain = domain, s = confident, POTENTIAL_TYPE = type)
newRange

# }