tbackfitting: Perform backfitting starting at output of 'tgreedy'.
In kkdey/flashr: Factor Loading Adaptive SHrinkage in R

Perform backfitting starting at output of tgreedy.

tbackfitting(Y, factor_list, sigma_est, maxiter_bf = 100, tol_bf = 10^-6,
  maxiter_vem = 100, var_type = c("homoscedastic", "kronecker"),
  mixcompdist = "normal", alpha = 0, beta = 0, nullweight = 10,
  known_factors = NULL, known_modes = NULL, homo_modes = NULL,
  tol_r1 = 10^-3)

`Y`	An array of numerics. The data.
`factor_list`	A list of matrices with the same number of columns. These are the starting values for the backfitting algorithm. The intended starting values are can be obtained from `tgreedy`.
`sigma_est`	Either a vector of estimated precisions (when `var_type = "homoscedastic"`) or a list of matrices whose columns are estimated precisions (when `var_type = "kronecker"`).
`maxiter_bf`	A positive integer. The maximum number of backfitting steps to perform.
`tol_bf`	A positive numeric. The stopping criterion for the backfitting algorithm.
`maxiter_vem`	A positive integer. The maximum number of steps in each VEM algorithm to perform at each iteration of the backfitting algorithm.
`var_type`	A string. What variance model should we assume? Options are homoscedastic noise (`"homoscedastic"`) or Kronecker structured variance (`kronecker`).
`mixcompdist`	The mixing distribution to assume. Defaults to normal. Options are those available in the `ashr` package.
`alpha`	A non-negative numeric. The prior shape parameter for the variance. Defaults to zero.
`beta`	A non-negative numeric. The prior rate parameter for the variance. Defaults to zero.
`nullweight`	A numeric greater than or equal to 1. The penalty term on the probability of zero.
`known_factors`	A list of known factors for the modes indicated in `known_modes`. Defaults to `NULL`, where all factors are assumed to be unknown.
`known_modes`	A vector of integers. The modes that are known. Should be the same length as `known_factors`.
`homo_modes`	A vector of integers. If `var_type = "kronecker"` then `homo_modes` indicates which modes are assumed to be homoscedastic.
`tol_r1`	A positive numeric. The tolerance for the rank 1 runs of tflash.