FunctionOptimization

interface FunctionOptimization<T : Any> : Optimization<T>
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A likelihood function optimization problem with provided derivatives

Types

Companion
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common
object Companion
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Functions

diffFunction
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common
abstract fun diffFunction(expression: DifferentiableExpression<T, Expression<T>>)
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Set a differentiable expression as objective function as function and gradient provider
initialGuess
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common
abstract fun initialGuess(map: Map<Symbol, T>)
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Define the initial guess for the optimization problem
optimize
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common
abstract fun optimize(): OptimizationResult<T>
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Make an optimization run
update
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abstract fun update(result: OptimizationResult<T>)
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Update the problem from previous optimization run

Properties

maximize
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abstract var maximize: Boolean
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The optimization direction.

Extensions

chiSquared
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fun <T : Any, I : Any, A : ExtendedField<I>, ExpressionAlgebra<T, I>> FunctionOptimization<T>.chiSquared(autoDiff: AutoDiffProcessor<T, I, A, Expression<T>>, x: Buffer<T>, y: Buffer<T>, yErr: Buffer<T>, model: A.(I) -> I)
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Define a chi-squared-based objective function