R/lotR.R

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

#' lotR:  **l**atent class analysis of  **o**bservations
#' organized by  **t**ree in  **R**
#'
#' `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.
#'
#' @seealso
#' \itemize{
#' \item <https://github.com/zhenkewu/lotR> for the source code
#' and system/software requirements to use `lotR` for your data.
#' }
#'
#' @section main lotR wrapper function:
#' [lcm_tree()]
#'
#' @docType package
#' @name lotR
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