Lattice-based space-filling designs with fill or separation distance properties including
  interleaved lattice-based minimax distance designs proposed in Xu He (2017) 
  <doi:10.1093/biomet/asx036>, interleaved lattice-based maximin distance designs 
  proposed in Xu He (2018) <doi:10.1093/biomet/asy069>, interleaved lattice-based 
  designs with low fill and high separation distance properties proposed in 
  Xu He (2024) <doi:10.1137/23M156940X>, (sliced) rotated sphere packing designs 
  proposed in Xu He (2017) <doi:10.1080/01621459.2016.1222289> and Xu He (2019) 
  <doi:10.1080/00401706.2018.1458655>, densest packing-based maximum projections 
  designs proposed in Xu He (2020) <doi:10.1093/biomet/asaa057> and Xu He (2018) 
  <doi:10.48550/arXiv.1709.02062>, maximin distance designs for mixed continuous, 
  ordinal, and binary variables proposed in Hui Lan and Xu He (2025) 
  <doi:10.48550/arXiv.2507.23405>, and optimized and regularly repeated lattice-based 
  Latin hypercube designs for large-scale computer experiments proposed in Xu He, 
  Junpeng Gong, and Zhaohui Li (2025) <doi:10.48550/arXiv.2506.04582>.

Building on the infrastructure provided by the lattice
	     package, this package provides several new high-level
	     functions and methods, as well as additional utilities
	     such as panel and axis annotation functions.

A general implementation of Structural Equation Models
	with latent variables (MLE, 2SLS, and composite likelihood
	estimators) with both continuous, censored, and ordinal
	outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>).
	Mixture latent variable models and non-linear latent variable models
	(Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>).
	The package also provides methods for graph exploration (d-separation,
	back-door criterion), simulation of general non-linear latent variable
	models, and estimation of influence functions for a broad range of
	statistical models.

Fit a variety of latent variable models, including confirmatory
   factor analysis, structural equation modeling and latent growth curve models.