Branching processes - applications











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Let's consider the population of parrots that come from the same female, where each female give birth to $n$ daughters with probability $p_n=frac{2}{3^{n+1}}, ;n=0,1,...$



(a)Find the probability of ultimate extinction,



(b)Find the probability, that extinction will exactly happen in 7th generation,



(c)Find the mean amount of females in $k$-th generation,



(d)Prove the formula for generating function of random variable $Z_k$, which is the amount of females in $k$-th generation



I need help with above-mentioned exercise. According (a) and (b) I know, that I need to find a generating function $G(s)= sum_{k=0}^{infty} P(Z_1=k)s^k$, but I'm not sure what I have to do with that knowledge. According to (c) and (d), I don't really know what am I supposed to do. Any help will be much appreciated.










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    Let's consider the population of parrots that come from the same female, where each female give birth to $n$ daughters with probability $p_n=frac{2}{3^{n+1}}, ;n=0,1,...$



    (a)Find the probability of ultimate extinction,



    (b)Find the probability, that extinction will exactly happen in 7th generation,



    (c)Find the mean amount of females in $k$-th generation,



    (d)Prove the formula for generating function of random variable $Z_k$, which is the amount of females in $k$-th generation



    I need help with above-mentioned exercise. According (a) and (b) I know, that I need to find a generating function $G(s)= sum_{k=0}^{infty} P(Z_1=k)s^k$, but I'm not sure what I have to do with that knowledge. According to (c) and (d), I don't really know what am I supposed to do. Any help will be much appreciated.










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      Let's consider the population of parrots that come from the same female, where each female give birth to $n$ daughters with probability $p_n=frac{2}{3^{n+1}}, ;n=0,1,...$



      (a)Find the probability of ultimate extinction,



      (b)Find the probability, that extinction will exactly happen in 7th generation,



      (c)Find the mean amount of females in $k$-th generation,



      (d)Prove the formula for generating function of random variable $Z_k$, which is the amount of females in $k$-th generation



      I need help with above-mentioned exercise. According (a) and (b) I know, that I need to find a generating function $G(s)= sum_{k=0}^{infty} P(Z_1=k)s^k$, but I'm not sure what I have to do with that knowledge. According to (c) and (d), I don't really know what am I supposed to do. Any help will be much appreciated.










      share|cite|improve this question















      Let's consider the population of parrots that come from the same female, where each female give birth to $n$ daughters with probability $p_n=frac{2}{3^{n+1}}, ;n=0,1,...$



      (a)Find the probability of ultimate extinction,



      (b)Find the probability, that extinction will exactly happen in 7th generation,



      (c)Find the mean amount of females in $k$-th generation,



      (d)Prove the formula for generating function of random variable $Z_k$, which is the amount of females in $k$-th generation



      I need help with above-mentioned exercise. According (a) and (b) I know, that I need to find a generating function $G(s)= sum_{k=0}^{infty} P(Z_1=k)s^k$, but I'm not sure what I have to do with that knowledge. According to (c) and (d), I don't really know what am I supposed to do. Any help will be much appreciated.







      probability-theory stochastic-processes random-variables






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      edited Nov 16 at 16:24









      Falrach

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      asked Nov 16 at 14:57









      MacAbra

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          The process you are looking at is a special type of the well known Galton Watson Process and the probability of extinction is characterized by the smallest fixpoint $eta$ of $G(s) = s$, where $sin [0,1]$.



          a) Solve $G(eta) = eta$.



          b) By evaluating the equation of d) at $0$ we get $Bbb P (Z_n = 0) = underbrace{G circ ldots circ G} _{n text{ times}}(0)$.



          c) Also well known : $Bbb E [Z_k] = (Bbb E [Z_1])^k$ (can be proved by induction)



          d) Prove by induction: $underbrace{G circ ldots circ G} _{n text{ times}} (s) = G_n(s):= sum_{k=0}^infty Bbb P (Z_n = k) s^k$



          The statements above are true for general Galton Watson Processes, but especially a) can be hard to solve. In your special case your can calculate $G$ explicitly:



          Assuming your definition of $p_n$ is a typo (otherwise this would not be a probability distribution) you can calculate the probability generating function as follows:



          $$G(s) = sum_{k=0}^{infty} Bbb P (Z_1 = k) s^k = sum_{k=0}^infty frac 2 {3^{k+1}} s^k = frac 2 3 sum_{k=0}^infty (frac s 3)^k = frac 2 3 frac 1 {1 - frac s 3} = frac 2 {3 -s}.$$






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          • What if instead of $n$ daughters there are $2$ daughters and with probability $frac35 $ each baby is female? Intuitively $G(s)= frac35 s^2 + frac35 s + frac35$, but then the probability of extinction is negative.
            – MacAbra
            Nov 24 at 11:38











          Your Answer





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          up vote
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          The process you are looking at is a special type of the well known Galton Watson Process and the probability of extinction is characterized by the smallest fixpoint $eta$ of $G(s) = s$, where $sin [0,1]$.



          a) Solve $G(eta) = eta$.



          b) By evaluating the equation of d) at $0$ we get $Bbb P (Z_n = 0) = underbrace{G circ ldots circ G} _{n text{ times}}(0)$.



          c) Also well known : $Bbb E [Z_k] = (Bbb E [Z_1])^k$ (can be proved by induction)



          d) Prove by induction: $underbrace{G circ ldots circ G} _{n text{ times}} (s) = G_n(s):= sum_{k=0}^infty Bbb P (Z_n = k) s^k$



          The statements above are true for general Galton Watson Processes, but especially a) can be hard to solve. In your special case your can calculate $G$ explicitly:



          Assuming your definition of $p_n$ is a typo (otherwise this would not be a probability distribution) you can calculate the probability generating function as follows:



          $$G(s) = sum_{k=0}^{infty} Bbb P (Z_1 = k) s^k = sum_{k=0}^infty frac 2 {3^{k+1}} s^k = frac 2 3 sum_{k=0}^infty (frac s 3)^k = frac 2 3 frac 1 {1 - frac s 3} = frac 2 {3 -s}.$$






          share|cite|improve this answer





















          • What if instead of $n$ daughters there are $2$ daughters and with probability $frac35 $ each baby is female? Intuitively $G(s)= frac35 s^2 + frac35 s + frac35$, but then the probability of extinction is negative.
            – MacAbra
            Nov 24 at 11:38















          up vote
          2
          down vote













          The process you are looking at is a special type of the well known Galton Watson Process and the probability of extinction is characterized by the smallest fixpoint $eta$ of $G(s) = s$, where $sin [0,1]$.



          a) Solve $G(eta) = eta$.



          b) By evaluating the equation of d) at $0$ we get $Bbb P (Z_n = 0) = underbrace{G circ ldots circ G} _{n text{ times}}(0)$.



          c) Also well known : $Bbb E [Z_k] = (Bbb E [Z_1])^k$ (can be proved by induction)



          d) Prove by induction: $underbrace{G circ ldots circ G} _{n text{ times}} (s) = G_n(s):= sum_{k=0}^infty Bbb P (Z_n = k) s^k$



          The statements above are true for general Galton Watson Processes, but especially a) can be hard to solve. In your special case your can calculate $G$ explicitly:



          Assuming your definition of $p_n$ is a typo (otherwise this would not be a probability distribution) you can calculate the probability generating function as follows:



          $$G(s) = sum_{k=0}^{infty} Bbb P (Z_1 = k) s^k = sum_{k=0}^infty frac 2 {3^{k+1}} s^k = frac 2 3 sum_{k=0}^infty (frac s 3)^k = frac 2 3 frac 1 {1 - frac s 3} = frac 2 {3 -s}.$$






          share|cite|improve this answer





















          • What if instead of $n$ daughters there are $2$ daughters and with probability $frac35 $ each baby is female? Intuitively $G(s)= frac35 s^2 + frac35 s + frac35$, but then the probability of extinction is negative.
            – MacAbra
            Nov 24 at 11:38













          up vote
          2
          down vote










          up vote
          2
          down vote









          The process you are looking at is a special type of the well known Galton Watson Process and the probability of extinction is characterized by the smallest fixpoint $eta$ of $G(s) = s$, where $sin [0,1]$.



          a) Solve $G(eta) = eta$.



          b) By evaluating the equation of d) at $0$ we get $Bbb P (Z_n = 0) = underbrace{G circ ldots circ G} _{n text{ times}}(0)$.



          c) Also well known : $Bbb E [Z_k] = (Bbb E [Z_1])^k$ (can be proved by induction)



          d) Prove by induction: $underbrace{G circ ldots circ G} _{n text{ times}} (s) = G_n(s):= sum_{k=0}^infty Bbb P (Z_n = k) s^k$



          The statements above are true for general Galton Watson Processes, but especially a) can be hard to solve. In your special case your can calculate $G$ explicitly:



          Assuming your definition of $p_n$ is a typo (otherwise this would not be a probability distribution) you can calculate the probability generating function as follows:



          $$G(s) = sum_{k=0}^{infty} Bbb P (Z_1 = k) s^k = sum_{k=0}^infty frac 2 {3^{k+1}} s^k = frac 2 3 sum_{k=0}^infty (frac s 3)^k = frac 2 3 frac 1 {1 - frac s 3} = frac 2 {3 -s}.$$






          share|cite|improve this answer












          The process you are looking at is a special type of the well known Galton Watson Process and the probability of extinction is characterized by the smallest fixpoint $eta$ of $G(s) = s$, where $sin [0,1]$.



          a) Solve $G(eta) = eta$.



          b) By evaluating the equation of d) at $0$ we get $Bbb P (Z_n = 0) = underbrace{G circ ldots circ G} _{n text{ times}}(0)$.



          c) Also well known : $Bbb E [Z_k] = (Bbb E [Z_1])^k$ (can be proved by induction)



          d) Prove by induction: $underbrace{G circ ldots circ G} _{n text{ times}} (s) = G_n(s):= sum_{k=0}^infty Bbb P (Z_n = k) s^k$



          The statements above are true for general Galton Watson Processes, but especially a) can be hard to solve. In your special case your can calculate $G$ explicitly:



          Assuming your definition of $p_n$ is a typo (otherwise this would not be a probability distribution) you can calculate the probability generating function as follows:



          $$G(s) = sum_{k=0}^{infty} Bbb P (Z_1 = k) s^k = sum_{k=0}^infty frac 2 {3^{k+1}} s^k = frac 2 3 sum_{k=0}^infty (frac s 3)^k = frac 2 3 frac 1 {1 - frac s 3} = frac 2 {3 -s}.$$







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Nov 16 at 15:56









          Falrach

          1,494223




          1,494223












          • What if instead of $n$ daughters there are $2$ daughters and with probability $frac35 $ each baby is female? Intuitively $G(s)= frac35 s^2 + frac35 s + frac35$, but then the probability of extinction is negative.
            – MacAbra
            Nov 24 at 11:38


















          • What if instead of $n$ daughters there are $2$ daughters and with probability $frac35 $ each baby is female? Intuitively $G(s)= frac35 s^2 + frac35 s + frac35$, but then the probability of extinction is negative.
            – MacAbra
            Nov 24 at 11:38
















          What if instead of $n$ daughters there are $2$ daughters and with probability $frac35 $ each baby is female? Intuitively $G(s)= frac35 s^2 + frac35 s + frac35$, but then the probability of extinction is negative.
          – MacAbra
          Nov 24 at 11:38




          What if instead of $n$ daughters there are $2$ daughters and with probability $frac35 $ each baby is female? Intuitively $G(s)= frac35 s^2 + frac35 s + frac35$, but then the probability of extinction is negative.
          – MacAbra
          Nov 24 at 11:38


















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