susiF.workhorse: Sum of Single Function
In stephenslab/susiF.alpha: Sum of Single Functions

susiF.workhorse

R Documentation

Sum of Single Function

Description

Implementation of the SuSiF method

Usage

susiF.workhorse(
  obj,
  W,
  X,
  tol,
  init_pi0_w,
  control_mixsqp,
  indx_lst,
  lowc_wc,
  nullweight,
  cal_obj,
  verbose,
  cov_lev,
  min_purity,
  maxit,
  tt,
  parallel = FALSE,
  max_SNP_EM = 500,
  max_step_EM = 1,
  cor_small = FALSE,
  is.pois = FALSE,
  e = 0.001
)

Arguments

`obj`	an object of class susiF
`W`	a list in which element D contains matrix of wavelet d coefficients and element C contains the vector of scaling coefficients
`X`	matrix of size n by p contains the covariates
`tol`	a small, non-negative number specifying the convergence tolerance for the IBSS fitting procedure. The fitting procedure will halt when the difference in the variational lower bound, or “ELBO” (the objective function to be maximized), is less than `tol`.
`init_pi0_w`	starting value of weight on null compoenent in mixsqp (between 0 and 1)
`control_mixsqp`	list of parameter for mixsqp function see mixsqp package
`indx_lst`	list generated by gen_wavelet_indx for the given level of resolution
`lowc_wc`	list of wavelet coefficients that exhibit too little variance
`nullweight`	numeric value for penalizing likelihood at point mass 0 (should be between 0 and 1) (usefull in small sample size)
`cal_obj`	logical if set as TRUE compute ELBO for convergence monitoring
`verbose`	If `verbose = TRUE`, the algorithm's progress, and a summary of the optimization settings are printed to the console.
`cov_lev`	numeric between 0 and 1, corresponding to the expected level of coverage of the cs if not specified set to 0.95
`min_purity`	minimum purity for estimated credible sets
`maxit`	Maximum number of IBSS iterations.
`tt`	output of the cal_Bhat_Shat function
`parallel`	if true use parallel computation
`max_SNP_EM`	check susiF description
`max_step_EM`	max_step_EM
`cor_small`	check susiF description
`is.pois`	check susiF description
`e`	threshold value to avoid computing posterior that have low alpha value. Set it to 0 to compute the entire posterio. default value is 0.001