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| alpha.compute | computes cumulative logistic coefficients using probabilities |
| attrib.dens | associates to a function of density parameter optimization an attribute to distinguish between ordinal and normal cases |
| dens.norm | computes the multinormal density of a given continuous measurement vector for all classes |
| dens.prod.ordi | computes the probability of a given discrete measurement vector for all classes under a product of multinomial |
| downward | performs the downward step of the peeling algorithm and computes unnormalized triplet and individual weights |
| downward.connect | performs a downward step for a connector |
| e.step | performs the E step of the EM algorithm for a single pedigree for both cases with and without familial dependence |
| init.norm | computes initial values for the EM algorithm in the case of continuous measurements |
| init.ordi | computes the initial values for EM algorithm in the case of ordinal measurements |
| init.p.trans | initializes the transition probabilities |
| lca.model | fits latent class models for phenotypic measurements in pedigrees with or without familial dependence using an Expectation-Maximization (EM) algorithm |
| 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 parameters in multinomial case, with an ordinal constraint on the parameters |
| optim.diff.norm | performs the M step for measurement density parameters in multinormal case |
| optim.equal.norm | performs the M step for measurement density parameters in multinormal case |
| optim.gene.norm | performs the M step for measurement density parameters in multinormal case |
| optim.indep.norm | performs the M step for measurement density parameters in multinormal case |
| optim.noconst.ordi | performs the M step for the measurement distribution parameters in multinomial case without constraint on the parameters |
| optim.probs | performs the M step of the EM algorithm for the probability parameters |
| p.compute | computes the probability vector using logistic coefficients |
| p.post.child | computes the posterior probability of observations of a child |
| p.post.found | computes the posterior probability of observations of a founder |
| param.cont | parameters to be used for examples in the case of continuous measurements |
| param.ordi | parameters to be used for examples in the case of discrete or ordinal measurements |
| ped.cont | pedigrees with continuous data to be used for examples |
| ped.ordi | pedigrees with discrete or ordinal data to be used for examples |
| peel | peeling order of pedigrees and couples in pedigrees |
| probs | probabilities parameters to be used for examples |
| upward | performs the upward step of the peeling algorithm of a pedigree |
| upward.connect | performs the upward step for a connector |
| weight.famdep | performs the computation of triplet and individual weights for a pedigree under familial dependence |
| weight.nuc | performs the computation of unnormalized triplet and individuals weights for a nuclear family in the pedigree |