maximumLogLikelihood
suspend fun Optimizer<Double, FunctionOptimization<Double>>.maximumLogLikelihood(problem: XYFit): XYFit(source)
Optimize given XY (least squares) problem using this function Optimizer. The problem is treated as maximum likelihood problem and is done via maximizing logarithmic likelihood, respecting possible weight dependency on the model and parameters.
suspend fun Optimizer<Double, FunctionOptimization<Double>>.maximumLogLikelihood(data: XYColumnarData<Double, Double, Double>, model: DifferentiableExpression<Double>, builder: XYOptimizationBuilder.() -> Unit): XYFit(source)