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<div class="breadcrumbs"><a href="../../index.html">kmath-optimization</a><span class="delimiter">/</span><a href="../index.html">space.kscience.kmath.optimization</a><span class="delimiter">/</span><span class="current">QowOptimizer</span></div>
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<h1 class="cover"><span>Qow</span><wbr><span><span>Optimizer</span></span></h1>
<div class="platform-hinted " data-platform-hinted="data-platform-hinted"><div class="content sourceset-dependent-content" data-active="" data-togglable=":kmath-optimization:dokkaHtmlPartial/commonMain"><div class="symbol monospace"><div class="block"><div class="block"><span class="token annotation builtin">@</span><a href="../../../kmath-memory/space.kscience.kmath/-unstable-k-math-a-p-i/index.html"><span class="token annotation builtin">UnstableKMathAPI</span></a></div></div><span class="token keyword">object </span><a href="index.html">QowOptimizer</a> : <a href="../-optimizer/index.html">Optimizer</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double/index.html">Double</a><span class="token punctuation">, </span><span class="token keyword"></span><a href="../-x-y-fit/index.html">XYFit</a><span class="token operator">&gt; </span><span class="clearfix"><span class="floating-right">(<a href="https://github.com/SciProgCentre/kmath/tree/master/kmath-optimization/src/commonMain/kotlin/space/kscience/kmath/optimization/QowOptimizer.kt#L33">source</a>)</span></span></div><p class="paragraph">An optimizer based onf Fyodor Tkachev's quasi-optimal weights method. See <a href="http://arxiv.org/abs/physics/0604127">the article</a>.</p></div></div>
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<h2 class="">Functions</h2>
<div class="table"><a data-name="-1022385861%2FFunctions%2F959727596" anchor-label="maximumLogLikelihood" id="-1022385861%2FFunctions%2F959727596" data-filterable-set=":kmath-optimization:dokkaHtmlPartial/commonMain"></a>
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<div><a href="../maximum-log-likelihood.html"><span>maximum</span><wbr><span>Log</span><wbr><span><span>Likelihood</span></span></a></div>
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<div class="platform-hinted " data-platform-hinted="data-platform-hinted"><div class="content sourceset-dependent-content" data-active="" data-togglable=":kmath-optimization:dokkaHtmlPartial/commonMain"><div class="symbol monospace"><div class="block"><div class="block"><span class="token annotation builtin">@</span><a href="../../../kmath-memory/space.kscience.kmath/-unstable-k-math-a-p-i/index.html"><span class="token annotation builtin">UnstableKMathAPI</span></a></div></div><span class="token keyword">suspend </span><span class="token keyword">fun </span><a href="../-optimizer/index.html">Optimizer</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double/index.html">Double</a><span class="token punctuation">, </span><span class="token keyword"></span><a href="../-function-optimization/index.html">FunctionOptimization</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double/index.html">Double</a><span class="token operator">&gt;</span><span class="token operator">&gt;</span><span class="token punctuation">.</span><a href="../maximum-log-likelihood.html"><span class="token function">maximumLogLikelihood</span></a><span class="token punctuation">(</span><span class="parameters "><span class="parameter ">problem<span class="token operator">: </span><a href="../-x-y-fit/index.html">XYFit</a></span></span><span class="token punctuation">)</span><span class="token operator">: </span><a href="../-x-y-fit/index.html">XYFit</a></div><div class="brief "><p class="paragraph">Optimize given XY (least squares) <a href="../maximum-log-likelihood.html">problem</a> using this function <a href="../-optimizer/index.html">Optimizer</a>. The problem is treated as maximum likelihood problem and is done via maximizing logarithmic likelihood, respecting possible weight dependency on the model and parameters.</p></div><div class="symbol monospace"><div class="block"><div class="block"><span class="token annotation builtin">@</span><a href="../../../kmath-memory/space.kscience.kmath/-unstable-k-math-a-p-i/index.html"><span class="token annotation builtin">UnstableKMathAPI</span></a></div></div><span class="token keyword">suspend </span><span class="token keyword">fun </span><a href="../-optimizer/index.html">Optimizer</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double/index.html">Double</a><span class="token punctuation">, </span><span class="token keyword"></span><a href="../-function-optimization/index.html">FunctionOptimization</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double/index.html">Double</a><span class="token operator">&gt;</span><span class="token operator">&gt;</span><span class="token punctuation">.</span><a href="../maximum-log-likelihood.html"><span class="token function">maximumLogLikelihood</span></a><span class="token punctuation">(</span><span class="parameters "><span class="parameter ">data<span class="token operator">: </span><a href="../../../kmath-core/space.kscience.kmath.data/-x-y-columnar-data/index.html">XYColumnarData</a><span class="token operator">&lt;</span><span class="token keyword"></span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double/index.html">Double</a><span class="token punctuation">, </span><span class="token keyword"></span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double/index.html">Double</a><span class="token punctuation">, </span><span class="token keyword"></span><a href="https://kotlinlang.org/api/latest/jvm/stdlib/kotlin/-double/index.html">Double</a><span class="token operator">&gt;</span><span class="token punctuation">, </span></span><span class="parameter ">model<span class="token operator">: </span><a href="../../../kmath-core/space.kscience.kmath.expressions/-di
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