Create a control structure for running EM algorithms

em.control(ctrl = NULL, ...)

Arguments

nplot

how often to plot wages of comparaison to model0

ncat

how often to log information

maxiter

maximum number of iterations

model_var

whether to allow for flexible variance (default is TRUE)

est_Amb

TBD

cstr_type

defines the type of constraints on the means for estimation

cstr_val

TBD

tol

tolerance for stopping the EM

tau

posterior likelihood to use instead of computing them using initial parameters

model0

model to compare estimation to when plotting

presp=1e-9

TBD

rel_weight

setting a particular weight for stayers versus movers (default is 1)

est_rho

vector of TRUE/FALSE that states which rho should be estimated

rho_in_diff

whether to estimate rho in level of in differences

dprior

Dirichlet prior for proportions (default 1.01)

nfirms_to_update=10,

number firms to update in probabilistic approach

proba_include

what terms to include in the liklihood for probabilistic approach (default to = c(1,1,1,1))

check_lik

whether to check the likelihood at each updating parameter

stochastic

whether to use stochastic EM instead of straight EM

fixb

when TRUE, imposes fixed interactions in different time periods

fixm

when TRUE, levels are not updated, only variances and proportions

deps=1e-50

TBD

file_backup_prefix

TBD

sd_floor=

floor imposed on all standard deviations (default is 1e-10)

posterior_reg

term added to posterior probablities (this is to deal with numerical issues, default is 1e-9)

textapp

text to show in logging

sdata_subsample

share of the stayers to use in estimation

sdata_subredraw

whether to redraw the subsample of stayers

vdec_sim_size

size to use in simulation

stayer_weight

weight attributed to stayers in joint estimation

est_rep=

number of starting values for EM

est_nbest

number of best starting values to select from using connectedness