<p>Two sequential estimators are proposed for the odds <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="362_2024_1639_Article_IEq1.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="69" /> </InlineMediaObject> <EquationSource Format="TEX">\(p/(1-p)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo stretchy="false">/</mo> <mo stretchy="false">(</mo> <mn>1</mn> <mo>-</mo> <mi>p</mi> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> and log odds <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="362_2024_1639_Article_IEq2.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="101" /> </InlineMediaObject> <EquationSource Format="TEX">\(\log (p/(1-p))\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>log</mo> <mo stretchy="false">(</mo> <mi>p</mi> <mo stretchy="false">/</mo> <mo stretchy="false">(</mo> <mn>1</mn> <mo>-</mo> <mi>p</mi> <mo stretchy="false">)</mo> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> respectively, using independent Bernoulli random variables with parameter <i>p</i> as inputs. The estimators are unbiased, and guarantee that the variance of the estimation error divided by the true value of the odds, or the variance of the estimation error of the log odds, are less than a target value for any <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="362_2024_1639_Article_IEq3.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="68" /> </InlineMediaObject> <EquationSource Format="TEX">\(p \in (0,1)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo>∈</mo> <mo stretchy="false">(</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation>. The estimators are close to optimal in the sense of Wolfowitz’s bound.</p>

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Estimating odds and log odds with guaranteed accuracy

  • Luis Mendo

摘要

Two sequential estimators are proposed for the odds \(p/(1-p)\) p / ( 1 - p ) and log odds \(\log (p/(1-p))\) log ( p / ( 1 - p ) ) respectively, using independent Bernoulli random variables with parameter p as inputs. The estimators are unbiased, and guarantee that the variance of the estimation error divided by the true value of the odds, or the variance of the estimation error of the log odds, are less than a target value for any \(p \in (0,1)\) p ( 0 , 1 ) . The estimators are close to optimal in the sense of Wolfowitz’s bound.