<p>Let <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="78" /> </InlineMediaObject> <EquationSource Format="TEX">\(X_1,X_2, \ldots \)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>X</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>X</mi> <mn>2</mn> </msub> <mo>,</mo> <mo>…</mo> </mrow> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq2.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="69" /> </InlineMediaObject> <EquationSource Format="TEX">\(Y_1, Y_2, \ldots \)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>Y</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>Y</mi> <mn>2</mn> </msub> <mo>,</mo> <mo>…</mo> </mrow> </math></EquationSource> </InlineEquation> be i.i.d. random uniform points in a bounded domain <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq3.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="54" /> </InlineMediaObject> <EquationSource Format="TEX">\(A \subset \mathbb {R}^2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>A</mi> <mo>⊂</mo> <msup> <mrow> <mi mathvariant="double-struck">R</mi> </mrow> <mn>2</mn> </msup> </mrow> </math></EquationSource> </InlineEquation> with smooth or polygonal boundary. Given <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq4.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="84" /> </InlineMediaObject> <EquationSource Format="TEX">\(n,m,k \in \mathbb {N}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo>,</mo> <mi>k</mi> <mo>∈</mo> <mi mathvariant="double-struck">N</mi> </mrow> </math></EquationSource> </InlineEquation>, define the <i>two-sample k-coverage threshold</i> <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq5.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="46" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{n,m,k}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>R</mi> <mrow> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> </math></EquationSource> </InlineEquation> to be the smallest <i>r</i> such that each point of <InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq6.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="98" /> </InlineMediaObject> <EquationSource Format="TEX">\( \{Y_1,\ldots ,Y_m\}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">{</mo> <msub> <mi>Y</mi> <mn>1</mn> </msub> <mo>,</mo> <mo>…</mo> <mo>,</mo> <msub> <mi>Y</mi> <mi>m</mi> </msub> <mo stretchy="false">}</mo> </mrow> </math></EquationSource> </InlineEquation> is covered at least <i>k</i> times by the disks of radius <i>r</i> centred on <InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq7.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="82" /> </InlineMediaObject> <EquationSource Format="TEX">\(X_1,\ldots ,X_n\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>X</mi> <mn>1</mn> </msub> <mo>,</mo> <mo>…</mo> <mo>,</mo> <msub> <mi>X</mi> <mi>n</mi> </msub> </mrow> </math></EquationSource> </InlineEquation>. We obtain the limiting distribution of <InlineEquation ID="IEq8"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq5.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="46" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{n,m,k}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>R</mi> <mrow> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> </math></EquationSource> </InlineEquation> as <InlineEquation ID="IEq9"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq9.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="58" /> </InlineMediaObject> <EquationSource Format="TEX">\(n \rightarrow \infty \)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>n</mi> <mo stretchy="false">→</mo> <mi>∞</mi> </mrow> </math></EquationSource> </InlineEquation> with <InlineEquation ID="IEq10"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq10.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="120" /> </InlineMediaObject> <EquationSource Format="TEX">\(m= m(n) \sim \tau n\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>m</mi> <mo>=</mo> <mi>m</mi> <mo stretchy="false">(</mo> <mi>n</mi> <mo stretchy="false">)</mo> <mo>∼</mo> <mi>τ</mi> <mi>n</mi> </mrow> </math></EquationSource> </InlineEquation> for some constant <InlineEquation ID="IEq11"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq11.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="42" /> </InlineMediaObject> <EquationSource Format="TEX">\(\tau &gt;0\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>τ</mi> <mo>&gt;</mo> <mn>0</mn> </mrow> </math></EquationSource> </InlineEquation>, with <i>k</i> fixed. If <i>A</i> has unit area, then <InlineEquation ID="IEq12"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq12.gif" Format="GIF" Height="24" Rendition="HTML" Resolution="72" Type="Linedraw" Width="137" /> </InlineMediaObject> <EquationSource Format="TEX">\(n \pi R_{n,m(n),1}^2 - \log n\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>n</mi> <mi>π</mi> <msubsup> <mi>R</mi> <mrow> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo stretchy="false">(</mo> <mi>n</mi> <mo stretchy="false">)</mo> <mo>,</mo> <mn>1</mn> </mrow> <mn>2</mn> </msubsup> <mo>-</mo> <mo>log</mo> <mi>n</mi> </mrow> </math></EquationSource> </InlineEquation> is asymptotically Gumbel distributed with scale parameter 1 and location parameter <InlineEquation ID="IEq13"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq13.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="34" /> </InlineMediaObject> <EquationSource Format="TEX">\(\log \tau \)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>log</mo> <mi>τ</mi> </mrow> </math></EquationSource> </InlineEquation>. For <InlineEquation ID="IEq14"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq14.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="42" /> </InlineMediaObject> <EquationSource Format="TEX">\(k &gt;2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>k</mi> <mo>&gt;</mo> <mn>2</mn> </mrow> </math></EquationSource> </InlineEquation>, we find that <InlineEquation ID="IEq15"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq15.gif" Format="GIF" Height="24" Rendition="HTML" Resolution="72" Type="Linedraw" Width="276" /> </InlineMediaObject> <EquationSource Format="TEX">\(n \pi R_{n,m(n),k}^2 - \log n - (2k-3) \log \log n\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>n</mi> <mi>π</mi> <msubsup> <mi>R</mi> <mrow> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo stretchy="false">(</mo> <mi>n</mi> <mo stretchy="false">)</mo> <mo>,</mo> <mi>k</mi> </mrow> <mn>2</mn> </msubsup> <mo>-</mo> <mo>log</mo> <mi>n</mi> <mo>-</mo> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mi>k</mi> <mo>-</mo> <mn>3</mn> <mo stretchy="false">)</mo> </mrow> <mo>log</mo> <mo>log</mo> <mi>n</mi> </mrow> </math></EquationSource> </InlineEquation> is asymptotically Gumbel with scale parameter 2 and a more complicated location parameter involving the perimeter of <i>A</i>; boundary effects dominate when <InlineEquation ID="IEq16"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq14.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="42" /> </InlineMediaObject> <EquationSource Format="TEX">\(k &gt;2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>k</mi> <mo>&gt;</mo> <mn>2</mn> </mrow> </math></EquationSource> </InlineEquation>. For <InlineEquation ID="IEq17"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11009_2025_10165_Article_IEq17.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="41" /> </InlineMediaObject> <EquationSource Format="TEX">\(k=2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>k</mi> <mo>=</mo> <mn>2</mn> </mrow> </math></EquationSource> </InlineEquation> the limiting cdf is a two-component extreme value distribution with scale parameters 1 and 2. We also give analogous results for higher dimensions, where the boundary effects dominate for all <i>k</i>.</p>

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Covering One Point Process with Another

  • Frankie Higgs,
  • Mathew D. Penrose,
  • Xiaochuan Yang

摘要

Let \(X_1,X_2, \ldots \) X 1 , X 2 , and \(Y_1, Y_2, \ldots \) Y 1 , Y 2 , be i.i.d. random uniform points in a bounded domain \(A \subset \mathbb {R}^2\) A R 2 with smooth or polygonal boundary. Given \(n,m,k \in \mathbb {N}\) n , m , k N , define the two-sample k-coverage threshold \(R_{n,m,k}\) R n , m , k to be the smallest r such that each point of \( \{Y_1,\ldots ,Y_m\}\) { Y 1 , , Y m } is covered at least k times by the disks of radius r centred on \(X_1,\ldots ,X_n\) X 1 , , X n . We obtain the limiting distribution of \(R_{n,m,k}\) R n , m , k as \(n \rightarrow \infty \) n with \(m= m(n) \sim \tau n\) m = m ( n ) τ n for some constant \(\tau >0\) τ > 0 , with k fixed. If A has unit area, then \(n \pi R_{n,m(n),1}^2 - \log n\) n π R n , m ( n ) , 1 2 - log n is asymptotically Gumbel distributed with scale parameter 1 and location parameter \(\log \tau \) log τ . For \(k >2\) k > 2 , we find that \(n \pi R_{n,m(n),k}^2 - \log n - (2k-3) \log \log n\) n π R n , m ( n ) , k 2 - log n - ( 2 k - 3 ) log log n is asymptotically Gumbel with scale parameter 2 and a more complicated location parameter involving the perimeter of A; boundary effects dominate when \(k >2\) k > 2 . For \(k=2\) k = 2 the limiting cdf is a two-component extreme value distribution with scale parameters 1 and 2. We also give analogous results for higher dimensions, where the boundary effects dominate for all k.