% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/router.R
\name{smriti_impute}
\alias{smriti_impute}
\title{Smriti Automated Longitudinal Imputation}
\usage{
smriti_impute(data, time_cols, lambda = 0.5, robust = TRUE)
}
\arguments{
\item{data}{A data frame containing missing values.}

\item{time_cols}{A character vector or numeric vector specifying the
longitudinal columns.}

\item{lambda}{A numeric value specifying the penalty weight for the
Lagrangian constraint.}

\item{robust}{A logical value. Setting it to TRUE sacrifices a marginal
degree of asymptotic efficiency on perfect Gaussian data to secure
structural integrity against heavy-tailed skew (the robustness-efficiency
tradeoff).}
}
\value{
A data frame with imputed and structurally refined values.
}
\description{
This function performs an automated routing and refinement for longitudinal
missing data. It establishes a target covariance manifold from observed data,
performs initial machine learning imputation, and then projects the result
back toward the structural manifold using a Lagrangian constraint.
}
