infinitefactor-package: Bayesian Infinite Factor Models

In infinitefactor: Bayesian Infinite Factor Models

Description

Sampler and post-processing functions for semi-parametric Bayesian infinite factor models, motivated by the Multiplicative Gamma Shrinkage Prior of Bhattacharya and Dunson (2011) <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3419391/>. Contains component C++ functions for building samplers for linear and 2-way interaction factor models using the multiplicative gamma and Dirichlet-Laplace shrinkage priors. The package also contains post processing functions to return matrices that display rotational ambiguity to identifiability through successive application of orthogonalization procedures and resolution of column label and sign switching. This package was developed with the support of the National Institute of Environmental Health Sciences grant 1R01ES028804-01.

Details

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Perform sampling with the linearMGSP() and linearDL() functions for linear factor models, or interactionMGSP() and interactionDL() functions for factor regression models including 2-way interactions. See jointRot() or msf() for postprocessing.

Author(s)

Evan Poworoznek

Maintainer: Evan Poworoznek <[e-mail]>

References

Bhattacharya, Anirban, and David B. Dunson. "Sparse Bayesian infinite factor models." Biometrika (2011): 291-306.

Bhattacharya, Anirban, et al. "Dirichlet-Laplace priors for optimal shrinkage." Journal of the American Statistical Association 110.512 (2015): 1479-1490.

Ferrari, Federico, and David B. Dunson. "Bayesian Factor Analysis for Inference on Interactions." arXiv preprint arXiv:1904.11603 (2019).

Examples

k0 = 5
p = 20
n = 100

lambda = matrix(rnorm(p*k0, 0, 0.01), ncol = k0)
lambda[sample.int(p, 40, replace = TRUE) +
         p*(sample.int(k0, 40, replace = TRUE)-1)] = rnorm(40, 0, 1)
lambda[1:7, 1] = rnorm(7, 2, 0.5)
lambda[8:14, 2] = rnorm(7, -2, 0.5)
lambda[15:20, 3] = rnorm(6, 2, 0.5)
lambda[,4] = rnorm(p, 0, 0.5)
lambda[,5] = rnorm(p, 0, 0.5)
plotmat(varimax(lambda)[[1]])

X = matrix(rnorm(n*k0),n,k0)%*%t(lambda) + matrix(rnorm(n*p), n, p)

out = linearMGSP(X = X, nrun = 1000, burn = 500, adapt = FALSE)

aligned = jointRot(out$lambdaSamps, out$etaSamps)

plotmat(lmean(aligned$lambda))

infinitefactor documentation built on April 3, 2020, 5:09 p.m.