# Calibrate Polynomial-Tail Laplace (PTL) model prdictions for LCA analysis

### Description

Fits PTL models to randomly sampled pairs of the dataset, to enable prediction of PTL model parameter values based on hyperparameter `d`

.

### Usage

1 | ```
fitPTLmodel(x,nPairs=10000)
``` |

### Arguments

`x` |
Numeric data input array, standardised to range (0,1) |

`nPairs` |
Numeric value specifying the number of samplings of pairs of objects to use to obtain hyperparameter fits |

### Details

Evaluates parameters for PTL model fits to the distributions of feature-wise differences between each of a specified (large) number of pairs of objects represented in dataset `x`

. Obtains subsequent model fits explaining the individual PTL parameters `alpha`

,`beta`

,`gamma`

in terms of the global (Euclidean) distances between the corresponding pairs of objects.

### Value

List with the following components:

`alpha` |
Object of class |

`beta` |
Object of class |

`gamma` |
Object of class |

### Author(s)

Ed Curry e.curry@imperial.ac.uk