probs: probabilities parameters to be used for examples

In LCAextend: Latent Class Analysis (LCA) with Familial Dependence in Extended Pedigrees

Description

a list of probability parameters such as the probability that a founder is assigned to each class, the transition probabilities and the probability that a child is symptomatic.

Usage

data(probs)

Details

probs a list of probability parameters:

For models with familial dependence:

p

a probability vector, each p[c] is the probability that an symptomatic founder is in class c for c>=1,

p0

the probability that a founder without symptoms is in class 0,

p.trans

an array of dimension K times K+1 times K+1, where K is the number of latent classes of the model, and is such that p.trans[c_i,c_1,c_2] is the conditional probability that a symptomatic individual i is in class c_i given that his parents are in classes c_1 and c_2,

p0connect

a vector of length K, where p0connect[c] is the probability that a connector without symptoms is in class 0, given that one of his parents is in class c>=1 and the other in class 0,

p.found

the probability that a founder is symptomatic,

p.child

the probability that a child is symptomatic,

For models without familial dependence, all individuals are independent:

p

a probability vector, each p[c] is the probability that an symptomatic individual is in class c for c>=1,

p0

the probability that an individual without symptoms is in class 0,

p.aff

the probability that an individual is symptomatic,

Examples

data(probs)

LCAextend documentation built on May 2, 2019, 2:02 a.m.