#' Streaming EM Approximation algorithm---multilevel model: fixed and random
#' effects
#'
#' The \code{SEMA} package allows one to fit online, or in a data stream,
#' multilevel models including fixed and random intercepts and slopes.
#' The equation numbers refer to the equations in Raudenbush and Bryk
#' hierarchical linear models, 2nd edition.
#'
#' @section
#' The \code{SEMA} package includes the following functions:
#' \itemize{
#' \item \code{\link{build_dataset}}: creates a multilevel, long-form,
#' data set.
#' \item \code{\link{build_theta_j}}: creates all objects at the unit level.
#' \item \code{\link{create_theta_main}}: allows users to include own start
#' values.
#' \item \code{\link{is.sema}}: checks whether list is sema class.
#' \item \code{\link{sema_fit_df}}: Fits multilevel models, input a
#' data.frame, returns model parameters, units' parameters, and optional,
#' stores the model parameters during the updating process.
#' \item \code{\link{sema_fit_one}}: Fits multilevel models, input one data
#' vector, returns updated model and unit parameters.
#' \item \code{\link{sema_fit_set}}: Fits multilevel models, input one data
#' vector, returns updated model parameters and a list with all units'
#' parameters, one of them updated.
#' \item \code{\link{predict}}: predicts outcome based on the data of
#' the covariates.
#' \item \code{\link{ranef}}: returns a data frame with coefficients of
#' the random effects.
#' \item \code{\link{store_fixed_coef}}: stores the estimates of the
#' fixed effects coefficients.
#' \item \code{\link{store_random_var}}: stores the estimates of the
#' variance of the random effects.
#' \item \code{\link{store_resid_var}}: stores the estimate of residual
#' variance coefficients
#' \item \code{\link{summary_sema}}: returns a list with the number of
#' units, number of observations, estimates of the fixed effects
#' coefficients, estimates of the variance of the random effects and the
#' estimate of the residual variance
#' }
#'
"_PACKAGE"
#' document()
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