lori: main function: analysis and imputation of incomplete count...
In genevievelrobin/gammit: Low-Rank Interactions in Count Data with Covariates

Description Usage Arguments Value Examples

main function: analysis and imputation of incomplete count data tables using side information (row-column attributes).

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lori(Y, cov = NULL, lambda1 = NULL, lambda2 = NULL, intercept = F,
  reff = T, ceff = T, rank.max = 10, algo = c("alt", "mcgd"),
  thresh = 1e-05, maxit = 1000, trace.it = F)

`Y`	[matrix, data.frame] count table (nxp).
`cov`	[matrix, data.frame] design matrix (np*q) in order row1xcol1,row2xcol2,..,rownxcol1,row1xcol2,row2xcol2,...,...,rownxcolp
`lambda1`	[positive number] the regularization parameter for the interaction matrix.
`lambda2`	[positive number] the regularization parameter for the covariate effects.
`intercept`	[boolean] whether an intercept should be fitted, default value is FALSE
`reff`	[boolean] whether row effects should be fitted, default value is TRUE
`ceff`	[boolean] whether column effects should be fitted, default value is TRUE
`rank.max`	[integer] maximum rank of interaction matrix (smaller than min(n-1,p-1))
`algo`	type of algorithm to use, either one of "mcgd" (mixed coordinate gradient descent, adapted to large dimensions) or "alt" (alternating minimization, adapted to small dimensions)
`thresh`	[positive number] convergence tolerance of algorithm, by default `1e-6`.
`maxit`	[integer] maximum allowed number of iterations.
`trace.it`	[boolean] whether convergence information should be printed

A list with the following elements

`X`	nxp matrix of log of expected counts
`alpha`	row effects
`beta`	column effects
`epsilon`	covariate effects
`theta`	nxp matrix of row-column interactions
`imputed`	nxp matrix of imputed counts
`means`	nxp matrix of expected counts (exp(X))
`cov`	npxK matrix of covariates