Clustering computation in pair approximation model












1












$begingroup$


Let's consider a square lattice of cells. Each cell can be either occupied by a species (1 or 2) or be empty (0).
Each cell can be either in state 1, 2 or 0.



In the pair approximation model, I would like to compute the clustering of the
species, i.e. the clustering of the occupied cells ($+$). It is define as:




  • $C_{++} = frac{q_{+|+}}{rho_{+}} = frac{rho_{++}}{rho_{+}^2}$


Where





  • $q_{+|+}$ is the conditional probability to find an occupied cell in the surrounding cells knowing that the focal cell is occupied


  • $rho_+$ is the density of occupied cells in the landscape, defines as: $rho_+ = rho_1 + rho_2$

  • $rho_{++}$ is the density of occupied cell pairs in the landscape, defines as: $rho_{++} = rho_{11} + rho_{12} + rho_{21} + rho_{22}$


  • $q_{i|j} = frac{rho_{ij}}{rho_{i}}$



One approach successfully describes the clustering but the second does not and I
do not find why.



A first approach (Works)




  • $q_{+|+} = frac{rho_{++}}{rho_{+}}$


  • $rho_{++} = rho_{11} + rho_{12} + rho_{21} + rho_{22}$



Knowing that $rho_{12} = rho_{21}$:




  • $q_{+|+} = frac{rho_{11} + 2rho_{12} + rho_{22}}{rho_{1} + rho_{2}}$


Hence:



begin{align}
C_{++} & = frac{rho_{11} + 2rho_{12} + rho_{22}}{rho_{1} + rho_{2}} times frac{1}{rho_{+}} \
& = frac{rho_{11} + 2rho_{12} + rho_{22}}{(rho_{1} + rho_{2})^2}
end{align}



This approach works, I have checked it by running simulation of cellular
automata.



A second approach (Do not works)



Let's define $q_{+|+}$.



It is the probability for one cell of state $1$ to be surrounded by occupied
cells + the probability for one cell of state $2$ to be surrounded by occupied
cells. It means that:



$$
q_{+|+} = q_{+|1} + q_{+|2}
$$



and q_{+|1} and q_{+|2} can be defined as:




  • $q_{+|1} = q_{1|1} + q_{2|1}$

  • $q_{+|2} = q_{1|2} + q_{2|2}$


So:



begin{align}
q_{+|+} & = q_{1|1} + q_{2|1} + q_{1|2} + q_{2|2} \
& = frac{rho_{11}}{rho_{1}} frac{rho_{12}}{rho_{1}} + frac{rho_{21}}{rho_{2}} + frac{rho_{22}}{rho_{2}} \
& = frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}} \
& = frac{rho_{2}(rho_{11} + rho_{12})}{rho_{1}rho_{2}} + frac{rho_{1}(rho_{21} + rho_{22})}{rho_{1}rho_{2}} \
& = frac{rho_{2}(rho_{11} + rho_{12}) + rho_{1}(rho_{21} + rho_{22}) }{rho_{1}rho_{2}} \
end{align}



Obviously this formulation of $q_{+|+}$ is different for the first one. In
simulation, this formulation gives $C_{++}$ twice higher than with a first
approach.



I do not know what is the mistake in this approach but I guess that the following
assertion is false:



$$q_{+|+} = q_{1|1} + q_{2|1} + q_{1|2} + q_{2|2}$$



I would be very helpful for me to know why.










share|cite|improve this question











$endgroup$

















    1












    $begingroup$


    Let's consider a square lattice of cells. Each cell can be either occupied by a species (1 or 2) or be empty (0).
    Each cell can be either in state 1, 2 or 0.



    In the pair approximation model, I would like to compute the clustering of the
    species, i.e. the clustering of the occupied cells ($+$). It is define as:




    • $C_{++} = frac{q_{+|+}}{rho_{+}} = frac{rho_{++}}{rho_{+}^2}$


    Where





    • $q_{+|+}$ is the conditional probability to find an occupied cell in the surrounding cells knowing that the focal cell is occupied


    • $rho_+$ is the density of occupied cells in the landscape, defines as: $rho_+ = rho_1 + rho_2$

    • $rho_{++}$ is the density of occupied cell pairs in the landscape, defines as: $rho_{++} = rho_{11} + rho_{12} + rho_{21} + rho_{22}$


    • $q_{i|j} = frac{rho_{ij}}{rho_{i}}$



    One approach successfully describes the clustering but the second does not and I
    do not find why.



    A first approach (Works)




    • $q_{+|+} = frac{rho_{++}}{rho_{+}}$


    • $rho_{++} = rho_{11} + rho_{12} + rho_{21} + rho_{22}$



    Knowing that $rho_{12} = rho_{21}$:




    • $q_{+|+} = frac{rho_{11} + 2rho_{12} + rho_{22}}{rho_{1} + rho_{2}}$


    Hence:



    begin{align}
    C_{++} & = frac{rho_{11} + 2rho_{12} + rho_{22}}{rho_{1} + rho_{2}} times frac{1}{rho_{+}} \
    & = frac{rho_{11} + 2rho_{12} + rho_{22}}{(rho_{1} + rho_{2})^2}
    end{align}



    This approach works, I have checked it by running simulation of cellular
    automata.



    A second approach (Do not works)



    Let's define $q_{+|+}$.



    It is the probability for one cell of state $1$ to be surrounded by occupied
    cells + the probability for one cell of state $2$ to be surrounded by occupied
    cells. It means that:



    $$
    q_{+|+} = q_{+|1} + q_{+|2}
    $$



    and q_{+|1} and q_{+|2} can be defined as:




    • $q_{+|1} = q_{1|1} + q_{2|1}$

    • $q_{+|2} = q_{1|2} + q_{2|2}$


    So:



    begin{align}
    q_{+|+} & = q_{1|1} + q_{2|1} + q_{1|2} + q_{2|2} \
    & = frac{rho_{11}}{rho_{1}} frac{rho_{12}}{rho_{1}} + frac{rho_{21}}{rho_{2}} + frac{rho_{22}}{rho_{2}} \
    & = frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}} \
    & = frac{rho_{2}(rho_{11} + rho_{12})}{rho_{1}rho_{2}} + frac{rho_{1}(rho_{21} + rho_{22})}{rho_{1}rho_{2}} \
    & = frac{rho_{2}(rho_{11} + rho_{12}) + rho_{1}(rho_{21} + rho_{22}) }{rho_{1}rho_{2}} \
    end{align}



    Obviously this formulation of $q_{+|+}$ is different for the first one. In
    simulation, this formulation gives $C_{++}$ twice higher than with a first
    approach.



    I do not know what is the mistake in this approach but I guess that the following
    assertion is false:



    $$q_{+|+} = q_{1|1} + q_{2|1} + q_{1|2} + q_{2|2}$$



    I would be very helpful for me to know why.










    share|cite|improve this question











    $endgroup$















      1












      1








      1





      $begingroup$


      Let's consider a square lattice of cells. Each cell can be either occupied by a species (1 or 2) or be empty (0).
      Each cell can be either in state 1, 2 or 0.



      In the pair approximation model, I would like to compute the clustering of the
      species, i.e. the clustering of the occupied cells ($+$). It is define as:




      • $C_{++} = frac{q_{+|+}}{rho_{+}} = frac{rho_{++}}{rho_{+}^2}$


      Where





      • $q_{+|+}$ is the conditional probability to find an occupied cell in the surrounding cells knowing that the focal cell is occupied


      • $rho_+$ is the density of occupied cells in the landscape, defines as: $rho_+ = rho_1 + rho_2$

      • $rho_{++}$ is the density of occupied cell pairs in the landscape, defines as: $rho_{++} = rho_{11} + rho_{12} + rho_{21} + rho_{22}$


      • $q_{i|j} = frac{rho_{ij}}{rho_{i}}$



      One approach successfully describes the clustering but the second does not and I
      do not find why.



      A first approach (Works)




      • $q_{+|+} = frac{rho_{++}}{rho_{+}}$


      • $rho_{++} = rho_{11} + rho_{12} + rho_{21} + rho_{22}$



      Knowing that $rho_{12} = rho_{21}$:




      • $q_{+|+} = frac{rho_{11} + 2rho_{12} + rho_{22}}{rho_{1} + rho_{2}}$


      Hence:



      begin{align}
      C_{++} & = frac{rho_{11} + 2rho_{12} + rho_{22}}{rho_{1} + rho_{2}} times frac{1}{rho_{+}} \
      & = frac{rho_{11} + 2rho_{12} + rho_{22}}{(rho_{1} + rho_{2})^2}
      end{align}



      This approach works, I have checked it by running simulation of cellular
      automata.



      A second approach (Do not works)



      Let's define $q_{+|+}$.



      It is the probability for one cell of state $1$ to be surrounded by occupied
      cells + the probability for one cell of state $2$ to be surrounded by occupied
      cells. It means that:



      $$
      q_{+|+} = q_{+|1} + q_{+|2}
      $$



      and q_{+|1} and q_{+|2} can be defined as:




      • $q_{+|1} = q_{1|1} + q_{2|1}$

      • $q_{+|2} = q_{1|2} + q_{2|2}$


      So:



      begin{align}
      q_{+|+} & = q_{1|1} + q_{2|1} + q_{1|2} + q_{2|2} \
      & = frac{rho_{11}}{rho_{1}} frac{rho_{12}}{rho_{1}} + frac{rho_{21}}{rho_{2}} + frac{rho_{22}}{rho_{2}} \
      & = frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}} \
      & = frac{rho_{2}(rho_{11} + rho_{12})}{rho_{1}rho_{2}} + frac{rho_{1}(rho_{21} + rho_{22})}{rho_{1}rho_{2}} \
      & = frac{rho_{2}(rho_{11} + rho_{12}) + rho_{1}(rho_{21} + rho_{22}) }{rho_{1}rho_{2}} \
      end{align}



      Obviously this formulation of $q_{+|+}$ is different for the first one. In
      simulation, this formulation gives $C_{++}$ twice higher than with a first
      approach.



      I do not know what is the mistake in this approach but I guess that the following
      assertion is false:



      $$q_{+|+} = q_{1|1} + q_{2|1} + q_{1|2} + q_{2|2}$$



      I would be very helpful for me to know why.










      share|cite|improve this question











      $endgroup$




      Let's consider a square lattice of cells. Each cell can be either occupied by a species (1 or 2) or be empty (0).
      Each cell can be either in state 1, 2 or 0.



      In the pair approximation model, I would like to compute the clustering of the
      species, i.e. the clustering of the occupied cells ($+$). It is define as:




      • $C_{++} = frac{q_{+|+}}{rho_{+}} = frac{rho_{++}}{rho_{+}^2}$


      Where





      • $q_{+|+}$ is the conditional probability to find an occupied cell in the surrounding cells knowing that the focal cell is occupied


      • $rho_+$ is the density of occupied cells in the landscape, defines as: $rho_+ = rho_1 + rho_2$

      • $rho_{++}$ is the density of occupied cell pairs in the landscape, defines as: $rho_{++} = rho_{11} + rho_{12} + rho_{21} + rho_{22}$


      • $q_{i|j} = frac{rho_{ij}}{rho_{i}}$



      One approach successfully describes the clustering but the second does not and I
      do not find why.



      A first approach (Works)




      • $q_{+|+} = frac{rho_{++}}{rho_{+}}$


      • $rho_{++} = rho_{11} + rho_{12} + rho_{21} + rho_{22}$



      Knowing that $rho_{12} = rho_{21}$:




      • $q_{+|+} = frac{rho_{11} + 2rho_{12} + rho_{22}}{rho_{1} + rho_{2}}$


      Hence:



      begin{align}
      C_{++} & = frac{rho_{11} + 2rho_{12} + rho_{22}}{rho_{1} + rho_{2}} times frac{1}{rho_{+}} \
      & = frac{rho_{11} + 2rho_{12} + rho_{22}}{(rho_{1} + rho_{2})^2}
      end{align}



      This approach works, I have checked it by running simulation of cellular
      automata.



      A second approach (Do not works)



      Let's define $q_{+|+}$.



      It is the probability for one cell of state $1$ to be surrounded by occupied
      cells + the probability for one cell of state $2$ to be surrounded by occupied
      cells. It means that:



      $$
      q_{+|+} = q_{+|1} + q_{+|2}
      $$



      and q_{+|1} and q_{+|2} can be defined as:




      • $q_{+|1} = q_{1|1} + q_{2|1}$

      • $q_{+|2} = q_{1|2} + q_{2|2}$


      So:



      begin{align}
      q_{+|+} & = q_{1|1} + q_{2|1} + q_{1|2} + q_{2|2} \
      & = frac{rho_{11}}{rho_{1}} frac{rho_{12}}{rho_{1}} + frac{rho_{21}}{rho_{2}} + frac{rho_{22}}{rho_{2}} \
      & = frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}} \
      & = frac{rho_{2}(rho_{11} + rho_{12})}{rho_{1}rho_{2}} + frac{rho_{1}(rho_{21} + rho_{22})}{rho_{1}rho_{2}} \
      & = frac{rho_{2}(rho_{11} + rho_{12}) + rho_{1}(rho_{21} + rho_{22}) }{rho_{1}rho_{2}} \
      end{align}



      Obviously this formulation of $q_{+|+}$ is different for the first one. In
      simulation, this formulation gives $C_{++}$ twice higher than with a first
      approach.



      I do not know what is the mistake in this approach but I guess that the following
      assertion is false:



      $$q_{+|+} = q_{1|1} + q_{2|1} + q_{1|2} + q_{2|2}$$



      I would be very helpful for me to know why.







      ordinary-differential-equations conditional-probability clustering cellular-automata






      share|cite|improve this question















      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited Oct 3 '18 at 12:20







      Alain Danet

















      asked Oct 2 '18 at 13:03









      Alain DanetAlain Danet

      85




      85






















          1 Answer
          1






          active

          oldest

          votes


















          0












          $begingroup$

          Indeed, your assertion is wrong:



          $$q_{+|+}
          = frac{rho_{++}}{rho_{+}}
          = frac{rho_{11} + rho_{12} + rho_{21} + rho_{22}}{rho_{1} + rho_{2}}
          ne frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}}
          = frac{rho_{+1}}{rho_{1}} + frac{rho_{+2}}{rho_{2}}
          = q_{+|1} + q_{+|2}.
          $$



          In particular, if $rho_{1} = rho_{2}$, then $rho_{1} + rho_{2} = 2rho_{1} = 2rho_{2}$, and so the left hand side will work out to exactly $frac12$ times the right hand side.



          (The same will also happen if $q_{+|1} = q_{+|2}$; in particular, that means that the assertion will always be off by exactly a factor of $frac12$ for well mixed systems, where $q_{a|b} = rho_a$ for all states $a$ and $b$. On the other extreme, if the states 1 and 2 are highly clustered such that $rho_{12} = rho_{21} approx 0$, you can basically have $q_{+|1}$ and $q_{+|2}$ take any arbitrary values independently of each other and have $q_{+|+}$ be anywhere in between them, depending on the ratio of $rho_1$ and $rho_2$.)





          The source of your confusion seems to be a basic misunderstanding of conditional probabilities. In particular, while it's true that $mathrm{Pr}[A text{ or } B mid C] = mathrm{Pr}[A mid C] + mathrm{Pr}[B mid C]$ whenever $A$ and $B$ are mutually exclusive events, this additivity only holds when the probabilities are conditioned on the same event $C$. In deriving your incorrect formula, you've basically asserted that $mathrm{Pr}[C mid A text{ or } B] = mathrm{Pr}[C mid A] + mathrm{Pr}[C mid B]$, which does not hold except in degenerate cases.






          share|cite|improve this answer











          $endgroup$














            Your Answer





            StackExchange.ifUsing("editor", function () {
            return StackExchange.using("mathjaxEditing", function () {
            StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
            StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
            });
            });
            }, "mathjax-editing");

            StackExchange.ready(function() {
            var channelOptions = {
            tags: "".split(" "),
            id: "69"
            };
            initTagRenderer("".split(" "), "".split(" "), channelOptions);

            StackExchange.using("externalEditor", function() {
            // Have to fire editor after snippets, if snippets enabled
            if (StackExchange.settings.snippets.snippetsEnabled) {
            StackExchange.using("snippets", function() {
            createEditor();
            });
            }
            else {
            createEditor();
            }
            });

            function createEditor() {
            StackExchange.prepareEditor({
            heartbeatType: 'answer',
            autoActivateHeartbeat: false,
            convertImagesToLinks: true,
            noModals: true,
            showLowRepImageUploadWarning: true,
            reputationToPostImages: 10,
            bindNavPrevention: true,
            postfix: "",
            imageUploader: {
            brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
            contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
            allowUrls: true
            },
            noCode: true, onDemand: true,
            discardSelector: ".discard-answer"
            ,immediatelyShowMarkdownHelp:true
            });


            }
            });














            draft saved

            draft discarded


















            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f2939346%2fclustering-computation-in-pair-approximation-model%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown

























            1 Answer
            1






            active

            oldest

            votes








            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            0












            $begingroup$

            Indeed, your assertion is wrong:



            $$q_{+|+}
            = frac{rho_{++}}{rho_{+}}
            = frac{rho_{11} + rho_{12} + rho_{21} + rho_{22}}{rho_{1} + rho_{2}}
            ne frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}}
            = frac{rho_{+1}}{rho_{1}} + frac{rho_{+2}}{rho_{2}}
            = q_{+|1} + q_{+|2}.
            $$



            In particular, if $rho_{1} = rho_{2}$, then $rho_{1} + rho_{2} = 2rho_{1} = 2rho_{2}$, and so the left hand side will work out to exactly $frac12$ times the right hand side.



            (The same will also happen if $q_{+|1} = q_{+|2}$; in particular, that means that the assertion will always be off by exactly a factor of $frac12$ for well mixed systems, where $q_{a|b} = rho_a$ for all states $a$ and $b$. On the other extreme, if the states 1 and 2 are highly clustered such that $rho_{12} = rho_{21} approx 0$, you can basically have $q_{+|1}$ and $q_{+|2}$ take any arbitrary values independently of each other and have $q_{+|+}$ be anywhere in between them, depending on the ratio of $rho_1$ and $rho_2$.)





            The source of your confusion seems to be a basic misunderstanding of conditional probabilities. In particular, while it's true that $mathrm{Pr}[A text{ or } B mid C] = mathrm{Pr}[A mid C] + mathrm{Pr}[B mid C]$ whenever $A$ and $B$ are mutually exclusive events, this additivity only holds when the probabilities are conditioned on the same event $C$. In deriving your incorrect formula, you've basically asserted that $mathrm{Pr}[C mid A text{ or } B] = mathrm{Pr}[C mid A] + mathrm{Pr}[C mid B]$, which does not hold except in degenerate cases.






            share|cite|improve this answer











            $endgroup$


















              0












              $begingroup$

              Indeed, your assertion is wrong:



              $$q_{+|+}
              = frac{rho_{++}}{rho_{+}}
              = frac{rho_{11} + rho_{12} + rho_{21} + rho_{22}}{rho_{1} + rho_{2}}
              ne frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}}
              = frac{rho_{+1}}{rho_{1}} + frac{rho_{+2}}{rho_{2}}
              = q_{+|1} + q_{+|2}.
              $$



              In particular, if $rho_{1} = rho_{2}$, then $rho_{1} + rho_{2} = 2rho_{1} = 2rho_{2}$, and so the left hand side will work out to exactly $frac12$ times the right hand side.



              (The same will also happen if $q_{+|1} = q_{+|2}$; in particular, that means that the assertion will always be off by exactly a factor of $frac12$ for well mixed systems, where $q_{a|b} = rho_a$ for all states $a$ and $b$. On the other extreme, if the states 1 and 2 are highly clustered such that $rho_{12} = rho_{21} approx 0$, you can basically have $q_{+|1}$ and $q_{+|2}$ take any arbitrary values independently of each other and have $q_{+|+}$ be anywhere in between them, depending on the ratio of $rho_1$ and $rho_2$.)





              The source of your confusion seems to be a basic misunderstanding of conditional probabilities. In particular, while it's true that $mathrm{Pr}[A text{ or } B mid C] = mathrm{Pr}[A mid C] + mathrm{Pr}[B mid C]$ whenever $A$ and $B$ are mutually exclusive events, this additivity only holds when the probabilities are conditioned on the same event $C$. In deriving your incorrect formula, you've basically asserted that $mathrm{Pr}[C mid A text{ or } B] = mathrm{Pr}[C mid A] + mathrm{Pr}[C mid B]$, which does not hold except in degenerate cases.






              share|cite|improve this answer











              $endgroup$
















                0












                0








                0





                $begingroup$

                Indeed, your assertion is wrong:



                $$q_{+|+}
                = frac{rho_{++}}{rho_{+}}
                = frac{rho_{11} + rho_{12} + rho_{21} + rho_{22}}{rho_{1} + rho_{2}}
                ne frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}}
                = frac{rho_{+1}}{rho_{1}} + frac{rho_{+2}}{rho_{2}}
                = q_{+|1} + q_{+|2}.
                $$



                In particular, if $rho_{1} = rho_{2}$, then $rho_{1} + rho_{2} = 2rho_{1} = 2rho_{2}$, and so the left hand side will work out to exactly $frac12$ times the right hand side.



                (The same will also happen if $q_{+|1} = q_{+|2}$; in particular, that means that the assertion will always be off by exactly a factor of $frac12$ for well mixed systems, where $q_{a|b} = rho_a$ for all states $a$ and $b$. On the other extreme, if the states 1 and 2 are highly clustered such that $rho_{12} = rho_{21} approx 0$, you can basically have $q_{+|1}$ and $q_{+|2}$ take any arbitrary values independently of each other and have $q_{+|+}$ be anywhere in between them, depending on the ratio of $rho_1$ and $rho_2$.)





                The source of your confusion seems to be a basic misunderstanding of conditional probabilities. In particular, while it's true that $mathrm{Pr}[A text{ or } B mid C] = mathrm{Pr}[A mid C] + mathrm{Pr}[B mid C]$ whenever $A$ and $B$ are mutually exclusive events, this additivity only holds when the probabilities are conditioned on the same event $C$. In deriving your incorrect formula, you've basically asserted that $mathrm{Pr}[C mid A text{ or } B] = mathrm{Pr}[C mid A] + mathrm{Pr}[C mid B]$, which does not hold except in degenerate cases.






                share|cite|improve this answer











                $endgroup$



                Indeed, your assertion is wrong:



                $$q_{+|+}
                = frac{rho_{++}}{rho_{+}}
                = frac{rho_{11} + rho_{12} + rho_{21} + rho_{22}}{rho_{1} + rho_{2}}
                ne frac{rho_{11} + rho_{12}}{rho_{1}} + frac{rho_{21} + rho_{22}}{rho_{2}}
                = frac{rho_{+1}}{rho_{1}} + frac{rho_{+2}}{rho_{2}}
                = q_{+|1} + q_{+|2}.
                $$



                In particular, if $rho_{1} = rho_{2}$, then $rho_{1} + rho_{2} = 2rho_{1} = 2rho_{2}$, and so the left hand side will work out to exactly $frac12$ times the right hand side.



                (The same will also happen if $q_{+|1} = q_{+|2}$; in particular, that means that the assertion will always be off by exactly a factor of $frac12$ for well mixed systems, where $q_{a|b} = rho_a$ for all states $a$ and $b$. On the other extreme, if the states 1 and 2 are highly clustered such that $rho_{12} = rho_{21} approx 0$, you can basically have $q_{+|1}$ and $q_{+|2}$ take any arbitrary values independently of each other and have $q_{+|+}$ be anywhere in between them, depending on the ratio of $rho_1$ and $rho_2$.)





                The source of your confusion seems to be a basic misunderstanding of conditional probabilities. In particular, while it's true that $mathrm{Pr}[A text{ or } B mid C] = mathrm{Pr}[A mid C] + mathrm{Pr}[B mid C]$ whenever $A$ and $B$ are mutually exclusive events, this additivity only holds when the probabilities are conditioned on the same event $C$. In deriving your incorrect formula, you've basically asserted that $mathrm{Pr}[C mid A text{ or } B] = mathrm{Pr}[C mid A] + mathrm{Pr}[C mid B]$, which does not hold except in degenerate cases.







                share|cite|improve this answer














                share|cite|improve this answer



                share|cite|improve this answer








                edited Feb 1 at 4:17

























                answered Feb 1 at 3:54









                Ilmari KaronenIlmari Karonen

                20.2k25186




                20.2k25186






























                    draft saved

                    draft discarded




















































                    Thanks for contributing an answer to Mathematics Stack Exchange!


                    • Please be sure to answer the question. Provide details and share your research!

                    But avoid



                    • Asking for help, clarification, or responding to other answers.

                    • Making statements based on opinion; back them up with references or personal experience.


                    Use MathJax to format equations. MathJax reference.


                    To learn more, see our tips on writing great answers.




                    draft saved


                    draft discarded














                    StackExchange.ready(
                    function () {
                    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f2939346%2fclustering-computation-in-pair-approximation-model%23new-answer', 'question_page');
                    }
                    );

                    Post as a guest















                    Required, but never shown





















































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown

































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown







                    Popular posts from this blog

                    android studio warns about leanback feature tag usage required on manifest while using Unity exported app?

                    SQL update select statement

                    'app-layout' is not a known element: how to share Component with different Modules