Aufgaben:Exercise 1.6: Transition Probabilities: Difference between revisions

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{{quiz-Header|Buchseite=Stochastische Signaltheorie/Markovketten
{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Markov_Chains
}}
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[[File:P_ID451__Sto_A_1_6.png|right|frame|20 Realisierungen der betrachteten Markovkette]]
[[File:EN_Sto_A_1_6.png|right|frame|$20$  Realizations of the considered Markov chain]]
Rechts sehen Sie 20 Realisierungen einer binären homogenen Markovkette erster Ordnung mit den Ereignissen $A$ und $B$:  
On the right you see  $20$  realizations of a binary homogeneous Markov chain of first order with the events  $A$  and  $B$:  
*Man erkennt bereits aus dieser Darstellung, dass zu Beginn ($ν = 0$) das Ereignis $A$ überwiegt.  
*One can already see from this representation that at the beginning  $(ν = 0)$  event  $A$  predominates.
*Zu späteren Zeitpunkten – etwa ab $ν = 4$ – tritt jedoch etwas häufiger das Ereignis $B$ auf.
*However,  at later times,  approximately from  $ν = 4$:  The event  $B$  occurs somewhat more frequently.




Durch Mittelung über Millionen von Realisierungen wurden einige Ereigniswahrscheinlichkeiten numerisch ermittelt:
By averaging over millions of realizations,  some event probabilities were determined numerically:


:$${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}0}) \approx 0.9, \hspace{0.3cm}{\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}1}) \approx 0.15, \hspace{0.3cm} {\rm Pr}(A_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) \approx 0.4.$$
:$${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}0}) \approx 0.9, \hspace{0.3cm}{\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}1}) \approx 0.15, \hspace{0.3cm} {\rm Pr}(A_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) \approx 0.4.$$


Diese empirischen Zahlenwerte sollen herangezogen werden, um die Parameter (Übergangswahrscheinlichkeiten) der Markovkette (näherungsweise) zu ermitteln.
These empirical numerical values will be used to determine (approximately) the  "transition probabilities"  of the Markov chain.




''Hinweise:''
 
*Die Aufgabe gehört zum  Kapitel [[Stochastische_Signaltheorie/Markovketten|Markovketten]].
 
 
 
Hints:  
*The exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/Markov_Chains|Markov Chains]].
   
   
*Sie können Ihre Ergebnisse mit dem interaktiven Applet [[Applets:Markovketten|Ereigniswahrscheinlichkeiten einer Markovkette 1. Ordnung]] überprüfen.
*You can check your results with the (German language) interactive SWF applet
: [[Applets:Markovketten|Ereigniswahrscheinlichkeiten einer Markov-Kette erster Ordnung]]   ⇒   "Event Probabilities of a First Order Markov Chain".






===Fragebogen===
===Questions===


<quiz display=simple>
<quiz display=simple>
{Welche Wahrscheinlichkeiten ergeben sich zu den Zeiten $ν = 0$, $ν = 1$ und $ν = 9$, wenn man nur die 20 dargestellten Realisierungen berücksichtigt?
{What are the probabilities at times&nbsp; $ν = 0$, &nbsp; $ν = 1$ &nbsp; and&nbsp; $ν = 9$, given&nbsp; only the&nbsp; $20$&nbsp; realizations shown?
|type="{}"}
|type="{}"}
${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}0}) \ = \ $  { 0.85 3% }
${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}0}) \ = \ $  { 0.85 3% }
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${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}9}) \ = \ $ { 0.4 3% }
${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}9}) \ = \ $ { 0.4 3% }


{Welche der Aussagen sind aufgrund der Musterfolgen zutreffend?
{Based on the pattern sequences,&nbsp; which of the statements are true?
|type="[]"}
|type="[]"}
+ Nach $A$ ist $B$ wahrscheinlicher als $A$.
+ After&nbsp; $A$:&nbsp; $B$&nbsp; is more probable than&nbsp; $A$.
+ Sowohl nach $A$ als auch nach $B$ kann wieder $A$ oder $B$ folgen.
+ After both&nbsp; $A$&nbsp; and&nbsp; $B$:&nbsp; $A$&nbsp; or&nbsp; $B$&nbsp; can follow again.
- Die Folge &bdquo;$B\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}\text{...}$&rdquo; ist nicht möglich.
- The sequence&nbsp; "$B\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}\text{...}$"&nbsp; is not possible.


{Berechnen Sie alle Übergangswahrscheinlichkeiten der Markovkette. Wie groß sind insbesondere ${\rm Pr}(A\hspace{0.05cm} | \hspace{0.05cm}A)$ und ${\rm Pr}(B\hspace{0.05cm} | \hspace{0.05cm}B)$?
{Calculate all transition probabilities of the Markov chain.&nbsp; In particular,&nbsp; how large are&nbsp; ${\rm Pr}(A\hspace{0.05cm} | \hspace{0.05cm}A)$&nbsp; and&nbsp; ${\rm Pr}(B\hspace{0.05cm} | \hspace{0.05cm}B)$?
|type="{}"}
|type="{}"}
${\rm Pr}(A\hspace{0.05cm} | \hspace{0.05cm}A) \ = \ $ { 0.1 3% }
${\rm Pr}(A\hspace{0.05cm} | \hspace{0.05cm}A) \ = \ $ { 0.1 3% }
${\rm Pr}(B\hspace{0.05cm} | \hspace{0.05cm}B) \ = \ $ { 0.4 3% }
${\rm Pr}(B\hspace{0.05cm} | \hspace{0.05cm}B) \ = \ $ { 0.4 3% }


{Wie groß ist die Wahrscheinlichkeit, dass die ersten zehn Elemente der Folge jeweils $B$ sind?
{What is the probability that the first ten elements of the sequence are each&nbsp; $B$&nbsp;?
|type="{}"}
|type="{}"}
${\rm Pr}(B_0, \hspace{0.05cm}\text{...}\hspace{0.05cm} , B_9)\ = \ $ { 2.62 3% } $\ \cdot  10^{-5}$
${\rm Pr}(B_0, \hspace{0.05cm}\text{...}\hspace{0.05cm} , B_9)\ = \ $ { 2.62 3% } $\ \cdot  10^{-5}$




{Wie groß ist die Wahrscheinlichkeit, dass sehr lange nach Einschalten der Kette die Zeichenfolge &bdquo;$A\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}A$&rdquo; erzeugt wird?
{What is the probability that the string&nbsp; "$A\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}A$"&nbsp; is generated a very long time after the chain is switched on?
|type="{}"}
|type="{}"}
${\rm Pr}(A\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}A)\ = \ $ { 8.64 3% } $\ \%$
${\rm Pr}(A\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}A)\ = \ $ { 8.64 3% } $\ \%$
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</quiz>
</quiz>


===Musterlösung===
===Solution===
{{ML-Kopf}}
{{ML-Kopf}}
'''(1)'''&nbsp; Die entsprechenden Wahrscheinlichkeiten sind:
'''(1)'''&nbsp; The corresponding probabilities are:
 
:$${\rm Pr}(A_{\nu=0}) = 17/20 \;\underline{= 0.85}, \hspace{0.2cm} {\rm Pr}(A_{\nu=1}) = 2/20 \;\underline{= 0.10}, \hspace{0.2cm} {\rm Pr}(A_{\nu=9}) = 8/20 \;\underline{= 0.40}.$$
 


:$${\rm Pr}(A_\text{v=0}) = 17/20 \;\underline{= 0.85}$&nbsp; ${\rm Pr}(A_\text{v=1}) = 2/20 \;\underline{= 0.10}$ &nbsp; ${\rm Pr}(A_\text{v=9}) = 8/20 \;\underline{= 0.840}.$$
'''(2)'''&nbsp; <u>Proposed solutions 1 and 2</u> are correct:
*$A$&nbsp; is followed by&nbsp; $B$&nbsp; much more frequently than by&nbsp; $A$,&nbsp; that is,&nbsp; it will certainly be&nbsp; ${\rm Pr}(B \hspace{0.05cm} | \hspace{0.05cm}A) > {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm}A)$.
*All four transitions between the two events&nbsp; $A$&nbsp; and&nbsp; $B$&nbsp; are possible.&nbsp; It follows that all four transition probabilities will be nonzero.
*Because of&nbsp; ${\rm Pr}(B_\text{v=0}) \ne 0$&nbsp; and&nbsp; ${\rm Pr}(B \hspace{0.05cm} | \hspace{0.05cm}B) \ne 0$,&nbsp; the sequence&nbsp; "$B\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{0.15cm}...$"&nbsp; can of course also be generated,&nbsp; even though it is not present in the twenty Markov chains output here.


'''(2)'''&nbsp; Richtig sind die <u> Lösungsvorschläge 1 und 2</u>:
*Nach $A$ folgt $B$ sehr viel h&auml;ufiger als $A$, das heißt, es wird sicher ${\rm Pr}(B \hspace{0.05cm} | \hspace{0.05cm}A) > {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm}A)$ sein.
*Alle vier &Uuml;berg&auml;nge zwischen den zwei Ereignissen $A$ und $B$ sind m&ouml;glich. Daraus folgt weiter, dass alle vier &Uuml;bergangswahrscheinlichkeiten ungleich $0$ sein werden.
*Wegen ${\rm Pr}(B_\text{v=0})  \ne 0$ und ${\rm Pr}(B \hspace{0.05cm} | \hspace{0.05cm}B) \ne 0$ kann nat&uuml;rlich auch die Folge &bdquo;$B\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}...$&rdquo; erzeugt werden, auch wenn diese bei den 20 hier ausgegebenen Markovketten nicht dabei ist.




'''(3)'''&nbsp; Bei einer Markovkette erster Ordnung gilt mit der Abk&uuml;rzung ${\rm Pr}(A_0) = {\rm Pr}(A_\text{v=0})$ usw.:
'''(3)'''&nbsp; For a first-order Markov chain,&nbsp; with the abbreviations&nbsp; ${\rm Pr}(A_0) = {\rm Pr}(A_{\nu=0})$&nbsp;  and&nbsp; ${\rm Pr}(A_1) = {\rm Pr}(A_{\nu=1})$:
:$${\rm Pr}(A_1) = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot {\rm Pr}(A_0) \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot {\rm Pr}(B_0).$$
:$${\rm Pr}(A_1) = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot {\rm Pr}(A_0) \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot {\rm Pr}(B_0).$$
Die ergodischen Wahrscheinlichkeiten sind ${\rm Pr}(A) = {\rm Pr}(A_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) = 0.4$ und ${\rm Pr}(B) = {\rm Pr}(B_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) = 0.6$. Zwischen diesen besteht folgender Zusammenhang:
*The ergodic probabilities are&nbsp; ${\rm Pr}(A) = {\rm Pr}(A_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) = 0.4$&nbsp; and&nbsp; ${\rm Pr}(B) = {\rm Pr}(B_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) = 0.6$.&nbsp; The following relationship exists between these:
:$${\rm Pr}(A) = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot {\rm Pr}(A) \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot {\rm Pr}(B).$$
:$${\rm Pr}(A) = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot {\rm Pr}(A) \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot {\rm Pr}(B).$$
Mit den angegebenen Zahlenwerten erh&auml;lt man aus diesen letzten beiden Gleichungen:  
*With the numerical values given,&nbsp; we obtain from these last two equations:
:$$0.15 = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot 0.90 \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot 0.10 ,$$
:$$0.15 = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot 0.90 \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot 0.10 ,$$
:$$0.40 = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot 0.40 \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot 0.60 .$$
:$$0.40 = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot 0.40 \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot 0.60 .$$
Multipliziert man die erste Gleichung mit $6$ und subtrahiert davon die zweite, so ergibt sich:  
*Multiplying the first equation by&nbsp; $6$&nbsp; and subtracting the second from it gives:
:$$0.5 = 5 \cdot {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \hspace{0.15cm} \Rightarrow
:$$0.5 = 5 \cdot {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \hspace{0.15cm} \Rightarrow\hspace{0.15cm}  {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \hspace{0.15cm}\underline {= 0.1}.$$
\hspace{0.15cm}  {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \hspace{0.15cm}\underline {= 0.1}.$$
*Substituting this result into one of the upper equations,&nbsp; we get&nbsp; $ {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}B) = 0.6$. The other probabilities are:
Setzt man dieses Ergebnis in eine der oberen Gleichungen ein, so erhält man $ {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}B) = 0.6$. Die weiteren Wahrscheinlichkeiten sind:
:$${\rm Pr}(B\hspace{0.05cm}|\hspace{0.05cm}A) = 1 - {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}A) = 0.9, \hspace{0.3cm}{\rm Pr}(B\hspace{0.05cm}|\hspace{0.05cm}B) = 1 - {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}B)\ \underline{= 0.4}.$$
$${\rm Pr}(B\hspace{0.05cm}|\hspace{0.05cm}A) = 1 - {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}A) = 0.9, \hspace{0.3cm}  
 
{\rm Pr}(B\hspace{0.05cm}|\hspace{0.05cm}B) = 1 - {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}B)\ \underline{= 0.4}.$$
 
 
'''(4)'''&nbsp; This case is only possible if the Markov chain starts with&nbsp; $B$&nbsp; and then there are nine transitions from&nbsp; $B$&nbsp; to&nbsp; $B$&nbsp;:
:$${\rm Pr}(B_0,\hspace{0.05cm}\text{...} \hspace{0.05cm}, B_{9}) = {\rm Pr}(B_0) \cdot {\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} B)^9 = {\rm 0.1} \cdot {\rm 0.4}^9 \hspace{0.15cm}\underline {\approx 2.62 \cdot 10^{-5}}. $$
 


'''(4)'''&nbsp; Dieser Fall ist nur dann m&ouml;glich, wenn die Markovkette mit $B$ beginnt und danach neunmal ein &Uuml;bergang von $B$ nach $B$ stattfindet:
:$${\rm Pr}(B_0,\hspace{0.05cm} ... \hspace{0.05cm}, B_{9}) = {\rm Pr}(B_0) \cdot {\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} B)^9 = {\rm 0.1} \cdot {\rm 0.4}^9 \hspace{0.15cm}\underline {\approx 2.62 \cdot 10^{-5}}. $$


'''(5)'''&nbsp; Hier muss von der ergodischen Wahrscheinlichkeit ${\rm Pr}(A)$ ausgegangen werden und man erh&auml;lt:
'''(5)'''&nbsp; Here we have to assume the ergodic probability&nbsp; ${\rm Pr}(A)$&nbsp; and we obtain:
:$${\rm Pr}(A_{\nu}, \hspace{0.05cm}B_{\nu +1}, \hspace{0.05cm}B_{\nu +2},\hspace{0.05cm} A_{\nu +3}) = {\rm Pr}(A) \hspace{0.01cm}\cdot \hspace{0.01cm}{\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} A) \hspace{0.01cm}\cdot\hspace{0.01cm} {\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} B)\hspace{0.01cm}\cdot \hspace{0.01cm}{\rm Pr}(A\hspace{0.05cm}| \hspace{0.05cm} B)\hspace{0.15cm}\underline {\approx 8.64 \% }.$$
:$${\rm Pr}(A_{\nu}, \hspace{0.05cm}B_{\nu +1}, \hspace{0.05cm}B_{\nu +2},\hspace{0.05cm} A_{\nu +3}) = {\rm Pr}(A) \hspace{0.01cm}\cdot \hspace{0.01cm}{\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} A) \hspace{0.01cm}\cdot\hspace{0.01cm} {\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} B)\hspace{0.01cm}\cdot \hspace{0.01cm}{\rm Pr}(A\hspace{0.05cm}| \hspace{0.05cm} B)\hspace{0.15cm}\underline {\approx 8.64 \% }.$$
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[[Category:Aufgaben zu Stochastische Signaltheorie|^1.4 Markovketten^]]
[[Category:Theory of Stochastic Signals: Exercises|^1.4 Markov Chains^]]
[[de:Aufgaben:Aufgabe 1.6: Übergangswahrscheinlichkeiten]]

Latest revision as of 17:56, 16 March 2026

$20$  Realizations of the considered Markov chain

On the right you see  $20$  realizations of a binary homogeneous Markov chain of first order with the events  $A$  and  $B$:

  • One can already see from this representation that at the beginning  $(ν = 0)$  event  $A$  predominates.
  • However,  at later times,  approximately from  $ν = 4$:  The event  $B$  occurs somewhat more frequently.


By averaging over millions of realizations,  some event probabilities were determined numerically:

$${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}0}) \approx 0.9, \hspace{0.3cm}{\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}1}) \approx 0.15, \hspace{0.3cm} {\rm Pr}(A_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) \approx 0.4.$$

These empirical numerical values will be used to determine (approximately) the  "transition probabilities"  of the Markov chain.




Hints:

  • You can check your results with the (German language) interactive SWF applet
Ereigniswahrscheinlichkeiten einer Markov-Kette erster Ordnung   ⇒   "Event Probabilities of a First Order Markov Chain".


Questions

1 What are the probabilities at times  $ν = 0$,   $ν = 1$   and  $ν = 9$, given  only the  $20$  realizations shown?

${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}0}) \ = \ $
${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}1}) \ = \ $
${\rm Pr}(A_{\nu \hspace{0.05cm} = \hspace{0.05cm}9}) \ = \ $

2 Based on the pattern sequences,  which of the statements are true?

After  $A$:  $B$  is more probable than  $A$.
After both  $A$  and  $B$:  $A$  or  $B$  can follow again.
The sequence  "$B\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}\text{...}$"  is not possible.

3 Calculate all transition probabilities of the Markov chain.  In particular,  how large are  ${\rm Pr}(A\hspace{0.05cm} | \hspace{0.05cm}A)$  and  ${\rm Pr}(B\hspace{0.05cm} | \hspace{0.05cm}B)$?

${\rm Pr}(A\hspace{0.05cm} | \hspace{0.05cm}A) \ = \ $
${\rm Pr}(B\hspace{0.05cm} | \hspace{0.05cm}B) \ = \ $

4 What is the probability that the first ten elements of the sequence are each  $B$ ?

${\rm Pr}(B_0, \hspace{0.05cm}\text{...}\hspace{0.05cm} , B_9)\ = \ $ $\ \cdot 10^{-5}$

5 What is the probability that the string  "$A\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}A$"  is generated a very long time after the chain is switched on?

${\rm Pr}(A\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}A)\ = \ $ $\ \%$


Solution

(1)  The corresponding probabilities are:

$${\rm Pr}(A_{\nu=0}) = 17/20 \;\underline{= 0.85}, \hspace{0.2cm} {\rm Pr}(A_{\nu=1}) = 2/20 \;\underline{= 0.10}, \hspace{0.2cm} {\rm Pr}(A_{\nu=9}) = 8/20 \;\underline{= 0.40}.$$


(2)  Proposed solutions 1 and 2 are correct:

  • $A$  is followed by  $B$  much more frequently than by  $A$,  that is,  it will certainly be  ${\rm Pr}(B \hspace{0.05cm} | \hspace{0.05cm}A) > {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm}A)$.
  • All four transitions between the two events  $A$  and  $B$  are possible.  It follows that all four transition probabilities will be nonzero.
  • Because of  ${\rm Pr}(B_\text{v=0}) \ne 0$  and  ${\rm Pr}(B \hspace{0.05cm} | \hspace{0.05cm}B) \ne 0$,  the sequence  "$B\hspace{-0.05cm}-\hspace{-0.05cm}B \hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{-0.05cm}B\hspace{-0.05cm}-\hspace{0.15cm}...$"  can of course also be generated,  even though it is not present in the twenty Markov chains output here.


(3)  For a first-order Markov chain,  with the abbreviations  ${\rm Pr}(A_0) = {\rm Pr}(A_{\nu=0})$  and  ${\rm Pr}(A_1) = {\rm Pr}(A_{\nu=1})$:

$${\rm Pr}(A_1) = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot {\rm Pr}(A_0) \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot {\rm Pr}(B_0).$$
  • The ergodic probabilities are  ${\rm Pr}(A) = {\rm Pr}(A_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) = 0.4$  and  ${\rm Pr}(B) = {\rm Pr}(B_{\nu \hspace{0.05cm} > \hspace{0.05cm}4}) = 0.6$.  The following relationship exists between these:
$${\rm Pr}(A) = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot {\rm Pr}(A) \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot {\rm Pr}(B).$$
  • With the numerical values given,  we obtain from these last two equations:
$$0.15 = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot 0.90 \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot 0.10 ,$$
$$0.40 = {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \cdot 0.40 \hspace{0.1cm} + \hspace{0.1cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} B) \cdot 0.60 .$$
  • Multiplying the first equation by  $6$  and subtracting the second from it gives:
$$0.5 = 5 \cdot {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \hspace{0.15cm} \Rightarrow\hspace{0.15cm} {\rm Pr}(A \hspace{0.05cm} | \hspace{0.05cm} A) \hspace{0.15cm}\underline {= 0.1}.$$
  • Substituting this result into one of the upper equations,  we get  $ {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}B) = 0.6$. The other probabilities are:
$${\rm Pr}(B\hspace{0.05cm}|\hspace{0.05cm}A) = 1 - {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}A) = 0.9, \hspace{0.3cm}{\rm Pr}(B\hspace{0.05cm}|\hspace{0.05cm}B) = 1 - {\rm Pr}(A\hspace{0.05cm}|\hspace{0.05cm}B)\ \underline{= 0.4}.$$


(4)  This case is only possible if the Markov chain starts with  $B$  and then there are nine transitions from  $B$  to  $B$ :

$${\rm Pr}(B_0,\hspace{0.05cm}\text{...} \hspace{0.05cm}, B_{9}) = {\rm Pr}(B_0) \cdot {\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} B)^9 = {\rm 0.1} \cdot {\rm 0.4}^9 \hspace{0.15cm}\underline {\approx 2.62 \cdot 10^{-5}}. $$


(5)  Here we have to assume the ergodic probability  ${\rm Pr}(A)$  and we obtain:

$${\rm Pr}(A_{\nu}, \hspace{0.05cm}B_{\nu +1}, \hspace{0.05cm}B_{\nu +2},\hspace{0.05cm} A_{\nu +3}) = {\rm Pr}(A) \hspace{0.01cm}\cdot \hspace{0.01cm}{\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} A) \hspace{0.01cm}\cdot\hspace{0.01cm} {\rm Pr}(B\hspace{0.05cm}| \hspace{0.05cm} B)\hspace{0.01cm}\cdot \hspace{0.01cm}{\rm Pr}(A\hspace{0.05cm}| \hspace{0.05cm} B)\hspace{0.15cm}\underline {\approx 8.64 \% }.$$