lotR: lotR: *l*atent class analysis of *o*bservations organized by...

In zhenkewu/lotR: Latent class analysis with Observed Trees in R (lotR)

lotR: latent class analysis of observations organized by tree in R

Description

lotR is designed for analyzing multivariate binary observations while integrating additional sample related information represented by each observation's membership in the leaves of a given tree. The observations that are closer in the tree are a priori more likely to be grouped together and fitted by a LCM with identical LCM parameters. The model is built on spike-and-slab priors on the increments of a Gaussian diffusion process for each node of the tree. The model is self-adaptive in that it automatically choose the optimal grouping of observations to fit distinct latent class models. The posterior inferential algorithm is based on variational inference and can provide approximate posterior uncertainty quantification.

main lotR wrapper function

lcm_tree()

See Also

• https://github.com/zhenkewu/lotR for the source code and system/software requirements to use lotR for your data.

zhenkewu/lotR documentation built on April 24, 2022, 2:36 a.m.