View source: R/learning_EM.R View source: R/RcppExports.R
m_cpp | R Documentation |
function to perform one step of the E-M algorithm
function to perform one step of the E-M algorithm
m_cpp(
e_step,
init_pars,
plugin,
lower_bound,
upper_bound,
xtol_rel,
num_threads,
rconditional = NULL
)
m_cpp(
e_step,
init_pars,
plugin,
lower_bound,
upper_bound,
xtol_rel,
num_threads,
rconditional = NULL
)
e_step |
result of e_step function, as a list |
init_pars |
vector of initial parameter values |
plugin |
string indicating plugin used, currently available: 'rpd1' and 'rpd5c' |
lower_bound |
vector of lower bound values for optimization, should be equal in length to the vector of init_pars |
upper_bound |
vector of upper bound values for optimization, should be equal in length to the vector of init_pars |
xtol_rel |
relative tolerance for optimization |
num_threads |
number of threads used. |
rconditional |
R function that evaluates the GAM function. |
list with the following entries:
estimatesvector of estimates
nloptnlopt status
timeused computation time
list with the following entries:
estimatesvector of estimates
nloptnlopt status
timeused computation time
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