This package performs a Latent Class Analysis of phenotypic measurements in pedigrees and a model selection based on one of two methods: likelihood-based cross-validation and Bayesian Information Criterion. It computes also individual and triplet child-parents weights in a pedigree using an upward-downward algorithm. It takes into account the familial dependence defined by the pedigree structure by considering that a class of a child depends on his parents classes via triplet-transition probabilities of the classes. The package handles the case where measurements are available on all subjects and the case where measurements are available only on symptomatic (i.e. affected) subjects. Distributions for discrete (or ordinal) and continuous data are currently implemented. The package can deal with missing data.

Author | Arafat TAYEB <arafat.tayeb@ircm.qc.ca>, Alexandre BUREAU <alexandre.bureau@msp.ulaval.ca> and Aurelie Labbe <aurelie.labbe@mcgill.ca> |

Date of publication | 2012-03-18 16:07:12 |

Maintainer | Alexandre BUREAU <alexandre.bureau@msp.ulaval.ca> |

License | GPL |

Version | 1.2 |

http://www.r-project.org, http://www.crulrg.ulaval.ca/pages_perso_chercheurs/bureau_a/ |

**alpha.compute:** computes cumulative logistic coefficients using probabilities

**attrib.dens:** associates to a function of density parameter optimization an...

**dens.norm:** computes the multinormal density of a given continuous...

**dens.prod.ordi:** computes the probability of a given discrete measurement...

**downward:** performs the downward step of the peeling algorithm and...

**downward.connect:** performs a downward step for a connector

**e.step:** performs the E step of the EM algorithm for a single pedigree...

**init.norm:** computes initial values for the EM algorithm in the case of...

**init.ordi:** computes the initial values for EM algorithm in the case of...

**init.p.trans:** initializes the transition probabilities

**LCAextend-package:** Latent Class Analysis (LCA) and model selection for pedigree...

**lca.model:** fits latent class models for phenotypic measurements in...

**model.select:** selects a latent class model for pedigree data

**n.param:** computes the number of parameters of a model

**optim.const.ordi:** performs the M step for the measurement distribution...

**optim.diff.norm:** performs the M step for measurement density parameters in...

**optim.equal.norm:** performs the M step for measurement density parameters in...

**optim.gene.norm:** performs the M step for measurement density parameters in...

**optim.indep.norm:** performs the M step for measurement density parameters in...

**optim.noconst.ordi:** performs the M step for the measurement distribution...

**optim.probs:** performs the M step of the EM algorithm for the probability...

**param.cont:** parameters to be used for examples in the case of continuous...

**param.ordi:** parameters to be used for examples in the case of discrete or...

**p.compute:** computes the probability vector using logistic coefficients

**ped.cont:** pedigrees with continuous data to be used for examples

**ped.ordi:** pedigrees with discrete or ordinal data to be used for...

**peel:** peeling order of pedigrees and couples in pedigrees

**p.post.child:** computes the posterior probability of observations of a child

**p.post.found:** computes the posterior probability of observations of a...

**probs:** probabilities parameters to be used for examples

**upward:** performs the upward step of the peeling algorithm of a...

**upward.connect:** performs the upward step for a connector

**weight.famdep:** performs the computation of triplet and individual weights...

**weight.nuc:** performs the computation of unnormalized triplet and...

LCAextend

LCAextend/MD5

LCAextend/man

LCAextend/man/weight.nuc.Rd
LCAextend/man/weight.famdep.Rd
LCAextend/man/upward.connect.Rd
LCAextend/man/upward.Rd
LCAextend/man/probs.Rd
LCAextend/man/peel.Rd
LCAextend/man/ped.ordi.Rd
LCAextend/man/ped.cont.Rd
LCAextend/man/param.ordi.Rd
LCAextend/man/param.cont.Rd
LCAextend/man/p.post.found.Rd
LCAextend/man/p.post.child.Rd
LCAextend/man/p.compute.Rd
LCAextend/man/optim.probs.Rd
LCAextend/man/optim.noconst.ordi.Rd
LCAextend/man/optim.indep.norm.Rd
LCAextend/man/optim.gene.norm.Rd
LCAextend/man/optim.equal.norm.Rd
LCAextend/man/optim.diff.norm.Rd
LCAextend/man/optim.const.ordi.Rd
LCAextend/man/n.param.Rd
LCAextend/man/model.select.Rd
LCAextend/man/lca.model.Rd
LCAextend/man/init.p.trans.Rd
LCAextend/man/init.ordi.Rd
LCAextend/man/init.norm.Rd
LCAextend/man/e.step.Rd
LCAextend/man/downward.connect.Rd
LCAextend/man/downward.Rd
LCAextend/man/dens.prod.ordi.Rd
LCAextend/man/dens.norm.Rd
LCAextend/man/attrib.dens.Rd
LCAextend/man/alpha.compute.Rd
LCAextend/man/LCAextend-package.Rd
LCAextend/data

LCAextend/data/probs.rda

LCAextend/data/peel.rda

LCAextend/data/ped.ordi.rda

LCAextend/data/ped.cont.rda

LCAextend/data/param.ordi.rda

LCAextend/data/param.cont.rda

LCAextend/R

LCAextend/R/weight.nuc.R
LCAextend/R/weight.famdep.R
LCAextend/R/upward.connect.R
LCAextend/R/upward.R
LCAextend/R/p.post.found.R
LCAextend/R/p.post.child.R
LCAextend/R/p.compute.R

LCAextend/R/optim.probs.R
LCAextend/R/optim.noconst.ordi.R
LCAextend/R/optim.indep.norm.R
LCAextend/R/optim.gene.norm.R
LCAextend/R/optim.equal.norm.R
LCAextend/R/optim.diff.norm.R
LCAextend/R/optim.const.ordi.R

LCAextend/R/n.param.R
LCAextend/R/model.select.R
LCAextend/R/lca.model.R

LCAextend/R/init.p.trans.R
LCAextend/R/init.ordi.R
LCAextend/R/init.norm.R
LCAextend/R/e.step.R
LCAextend/R/downward.connect.R
LCAextend/R/downward.R
LCAextend/R/dens.prod.ordi.R

LCAextend/R/dens.norm.R
LCAextend/R/attrib.dens.R
LCAextend/R/alpha.compute.R
LCAextend/NAMESPACE

LCAextend/DESCRIPTION

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