Difference between revisions of "Aufgaben:Exercise 4.7Z: Generation of a Joint PDF"

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[[File:P_ID423__Sto_Z_4_7.png|right|frame|Requirements for the generation of a <br>2D random variable]]
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[[File:P_ID423__Sto_Z_4_7.png|right|frame|Requirements for the generation of a <br>two-dimensional random variable]]
Given statistically independent quantities&nbsp; $u$&nbsp; and&nbsp; $v$, both of which are uniformly distributed between&nbsp; $-1$&nbsp; and&nbsp; $+1$&nbsp; and thus each have variance&nbsp; $\sigma^2 = 2/3$&nbsp;, generate a 2D random variable&nbsp; $(x, y)$&nbsp; where for the components:
+
Given statistically independent quantities&nbsp; $u$&nbsp; and&nbsp; $v$,  
 +
*both of which are uniformly distributed between&nbsp; $-1$&nbsp; and&nbsp; $+1$,&nbsp; and  
 +
*thus each have variance&nbsp; $\sigma^2 = 2/3$,&nbsp;  
 +
 
 +
 
 +
generate a two-dimensional random variable&nbsp; $(x,\hspace{0.08cm} y)$&nbsp; where for the components:
 
:$$x = A \cdot u + B \cdot v + C,$$
 
:$$x = A \cdot u + B \cdot v + C,$$
 
:$$y= D \cdot u + E \cdot v + F.$$
 
:$$y= D \cdot u + E \cdot v + F.$$
  
The 2D&ndash;random variable&nbsp; $(x, y)$&nbsp; to be generated should have the following statistical properties:
+
The two-dimensional random variable&nbsp; $(x,\hspace{0.08cm} y)$&nbsp; to be generated should have the following statistical properties:
 
* Let the variances be&nbsp; $\sigma_x^2 = 4$&nbsp; and&nbsp; $\sigma_y^2 = 10$.
 
* Let the variances be&nbsp; $\sigma_x^2 = 4$&nbsp; and&nbsp; $\sigma_y^2 = 10$.
 
* Let the random variable&nbsp; $x$&nbsp; be mean-free&nbsp; $(m_x =0)$.
 
* Let the random variable&nbsp; $x$&nbsp; be mean-free&nbsp; $(m_x =0)$.
* For the mean of&nbsp; $y$&nbsp; let&nbsp; $m_y = 1$ hold.
+
* For the mean of&nbsp; $y$&nbsp; let&nbsp; $m_y = 1$&nbsp; hold.
 
* The correlation coefficient between&nbsp; $x$&nbsp; and&nbsp; $y$&nbsp; is&nbsp; $\rho_{xy} = \sqrt{0.9} = 0.949.$
 
* The correlation coefficient between&nbsp; $x$&nbsp; and&nbsp; $y$&nbsp; is&nbsp; $\rho_{xy} = \sqrt{0.9} = 0.949.$
 
* The random variable&nbsp; $x$&nbsp; possess a triangular PDF $f_x(x)$&nbsp; corresponding to the above graph.
 
* The random variable&nbsp; $x$&nbsp; possess a triangular PDF $f_x(x)$&nbsp; corresponding to the above graph.
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+
Hints:  
 
 
 
 
''Hints:''
 
 
*The exercise belongs to the chapter&nbsp; [[Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables|Linear Combinations of Random Variables]].
 
*The exercise belongs to the chapter&nbsp; [[Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables|Linear Combinations of Random Variables]].
*In particular, reference is made to the page&nbsp; [Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables#Generation_of_correlated_random_variables|Generation of correlated random variables]].
+
*In particular,&nbsp; reference is made to the page&nbsp; [[Theory_of_Stochastic_Signals/Linear_Combinations_of_Random_Variables#Generation_of_correlated_random_variables|Generation of correlated random variables]].
*To avoid ambiguity, it is specified that all coefficients&nbsp; $A$, ... , $F$&nbsp; should be non-negative.
+
*To avoid ambiguity,&nbsp; it is specified that all coefficients&nbsp; $A$, ... , $F$&nbsp; should be non-negative.
 
   
 
   
  
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{Determine the coefficients&nbsp; $D$&nbsp; and&nbsp; $E$, where&nbsp; $D > E$&nbsp; should hold.
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{Determine the coefficients&nbsp; $D$&nbsp; and&nbsp; $E$,&nbsp; where&nbsp; $D > E$&nbsp; should hold.
 
|type="{}"}
 
|type="{}"}
 
$D \ = \ $ { 3.464 3% }
 
$D \ = \ $ { 3.464 3% }
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{Specify the maximum values for&nbsp; $x$&nbsp; and&nbsp; $y$&nbsp;.
+
{Specify the maximum values for&nbsp; $x$&nbsp; and&nbsp; $y$.
 
|type="{}"}
 
|type="{}"}
 
$x_\text{max}\ = \ $ { 3.464 3% }
 
$x_\text{max}\ = \ $ { 3.464 3% }
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===Solution===
 
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Given the mean values given, it must hold:  
+
'''(1)'''&nbsp; Given the mean values,&nbsp; it must hold:  
 
:$$ C = m_x\hspace{0.15cm}\underline{ = 0},$$
 
:$$ C = m_x\hspace{0.15cm}\underline{ = 0},$$
 
:$$ F = m_y\hspace{0.15cm}\underline{ = 1}.$$
 
:$$ F = m_y\hspace{0.15cm}\underline{ = 1}.$$
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:$$\sigma_x^2 = \sigma^2 \cdot ( A^2 + B^2)= {2}/{3} \cdot ( A^2 + B^2) .$$
 
:$$\sigma_x^2 = \sigma^2 \cdot ( A^2 + B^2)= {2}/{3} \cdot ( A^2 + B^2) .$$
  
*Because&nbsp; $\sigma_x^2 = 4$&nbsp; it follows&nbsp; $A^2 + B^2= 6$.  
+
*Because of&nbsp; $\sigma_x^2 = 4$&nbsp; it follows&nbsp; $A^2 + B^2= 6$.  
 
*A triangular PDF means that&nbsp; $A = \pm B$&nbsp; must hold.  
 
*A triangular PDF means that&nbsp; $A = \pm B$&nbsp; must hold.  
*Thus, since negative coefficients have been excluded, we obtain:  
+
*Thus,&nbsp; since negative coefficients have been excluded,&nbsp; we obtain:  
 
:$$ A = B = \sqrt{3}\hspace{0.15cm}\underline{ = 1.732}.$$
 
:$$ A = B = \sqrt{3}\hspace{0.15cm}\underline{ = 1.732}.$$
  
 
   
 
   
 
[[File:P_ID424__Sto_Z_4_7_d.png|right|frame|Rhombic joint PDF]]
 
[[File:P_ID424__Sto_Z_4_7_d.png|right|frame|Rhombic joint PDF]]
'''(3)'''&nbsp; With&nbsp; $ A = B = \sqrt{3}$&nbsp; corresponding to the last subtask, two equations of determination remain for&nbsp; $D$&nbsp; and&nbsp; $E$:
+
'''(3)'''&nbsp; With&nbsp; $ A = B = \sqrt{3}$&nbsp; corresponding to the last subtask,&nbsp; two equations of determination remain for&nbsp; $D$&nbsp; and&nbsp; $E$:
 
:$$\sigma_y^2 = \sigma^2 \cdot ( D^2 + E^2)= 10 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} D^2 + E^2 = \frac {\sigma_y^2}{\sigma^2} = \frac {10}{2/3} \stackrel{!}{=}15,$$
 
:$$\sigma_y^2 = \sigma^2 \cdot ( D^2 + E^2)= 10 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} D^2 + E^2 = \frac {\sigma_y^2}{\sigma^2} = \frac {10}{2/3} \stackrel{!}{=}15,$$
 
:$$\rho_{xy} = \frac{A \cdot D + B \cdot E}{\sqrt{(A^2 + B^2)(D^2 + E^2)}} = \frac{\sqrt{3} \cdot (D + E)}{\sqrt{6 \cdot (D^2 + E^2)}}  \stackrel{!}{=} \sqrt{0.9}.$$
 
:$$\rho_{xy} = \frac{A \cdot D + B \cdot E}{\sqrt{(A^2 + B^2)(D^2 + E^2)}} = \frac{\sqrt{3} \cdot (D + E)}{\sqrt{6 \cdot (D^2 + E^2)}}  \stackrel{!}{=} \sqrt{0.9}.$$
  
 
*From this it further follows:&nbsp; $D + E = \sqrt{1.8 \cdot ( D^2 + E^2)} = \sqrt{27} = 3 \cdot \sqrt{3}.$  
 
*From this it further follows:&nbsp; $D + E = \sqrt{1.8 \cdot ( D^2 + E^2)} = \sqrt{27} = 3 \cdot \sqrt{3}.$  
*The equation, in conjunction with&nbsp; $D^2 + E^2 = 15$&nbsp; and the constraint&nbsp; $(D>E)$&nbsp; leads to the result:
+
*The equation,&nbsp; in conjunction with&nbsp; $D^2 + E^2 = 15$&nbsp; and the constraint&nbsp; $(D>E)$&nbsp; leads to the result:
 
:$$ D= 2 \cdot \sqrt{3}\hspace{0.15cm}\underline{ = 3.464}, \hspace{0.5cm}E= \sqrt{3} \hspace{0.15cm}\underline{= 1.732}.$$
 
:$$ D= 2 \cdot \sqrt{3}\hspace{0.15cm}\underline{ = 3.464}, \hspace{0.5cm}E= \sqrt{3} \hspace{0.15cm}\underline{= 1.732}.$$
  
  
'''(4)'''&nbsp; The random variables&nbsp; $x$&nbsp; and&nbsp; $y$&nbsp; respectively, take their maximum values when respectively&nbsp; $u= +1$ and&nbsp; $v= +1$&nbsp; holds:
+
'''(4)'''&nbsp; The random variables&nbsp; $x$&nbsp; and&nbsp; $y$&nbsp; resp. take their maximum values when&nbsp; $u= +1$ and&nbsp; $v= +1$&nbsp; holds:
 
:$$ x_\text{max}= A+B \hspace{0.15cm}\underline{ = +3.464}, \hspace{0.5cm} x_\text{min} = - A - B= -3.464.$$
 
:$$ x_\text{max}= A+B \hspace{0.15cm}\underline{ = +3.464}, \hspace{0.5cm} x_\text{min} = - A - B= -3.464.$$
 
:$$ y_\text{max}= D+E+F \hspace{0.15cm}\underline{ = +6.196}, \hspace{0.5cm} y_\text{min} = -D-E+F= -4.196.$$
 
:$$ y_\text{max}= D+E+F \hspace{0.15cm}\underline{ = +6.196}, \hspace{0.5cm} y_\text{min} = -D-E+F= -4.196.$$

Latest revision as of 17:45, 25 February 2022

Requirements for the generation of a
two-dimensional random variable

Given statistically independent quantities  $u$  and  $v$,

  • both of which are uniformly distributed between  $-1$  and  $+1$,  and
  • thus each have variance  $\sigma^2 = 2/3$, 


generate a two-dimensional random variable  $(x,\hspace{0.08cm} y)$  where for the components:

$$x = A \cdot u + B \cdot v + C,$$
$$y= D \cdot u + E \cdot v + F.$$

The two-dimensional random variable  $(x,\hspace{0.08cm} y)$  to be generated should have the following statistical properties:

  • Let the variances be  $\sigma_x^2 = 4$  and  $\sigma_y^2 = 10$.
  • Let the random variable  $x$  be mean-free  $(m_x =0)$.
  • For the mean of  $y$  let  $m_y = 1$  hold.
  • The correlation coefficient between  $x$  and  $y$  is  $\rho_{xy} = \sqrt{0.9} = 0.949.$
  • The random variable  $x$  possess a triangular PDF $f_x(x)$  corresponding to the above graph.
  • The random variable  $y$  has a trapezoidal PDF $f_y(y)$  according to the lower graph.



Hints:


Questions

1

Determine the coefficients  $C$  and  $F$.

$C \ = \ $

$F\ = \ $

2

Determine the coefficients  $A$  and  $B$.

$A \ = \ $

$B \ = \ $

3

Determine the coefficients  $D$  and  $E$,  where  $D > E$  should hold.

$D \ = \ $

$E \ = \ $

4

Specify the maximum values for  $x$  and  $y$.

$x_\text{max}\ = \ $

$y_\text{max}\ = \ $


Solution

(1)  Given the mean values,  it must hold:

$$ C = m_x\hspace{0.15cm}\underline{ = 0},$$
$$ F = m_y\hspace{0.15cm}\underline{ = 1}.$$


(2)  Taking into account  $\sigma^2 = 2/3$  holds:

$$\sigma_x^2 = \sigma^2 \cdot ( A^2 + B^2)= {2}/{3} \cdot ( A^2 + B^2) .$$
  • Because of  $\sigma_x^2 = 4$  it follows  $A^2 + B^2= 6$.
  • A triangular PDF means that  $A = \pm B$  must hold.
  • Thus,  since negative coefficients have been excluded,  we obtain:
$$ A = B = \sqrt{3}\hspace{0.15cm}\underline{ = 1.732}.$$


Rhombic joint PDF

(3)  With  $ A = B = \sqrt{3}$  corresponding to the last subtask,  two equations of determination remain for  $D$  and  $E$:

$$\sigma_y^2 = \sigma^2 \cdot ( D^2 + E^2)= 10 \hspace{0.5cm} \Rightarrow \hspace{0.5cm} D^2 + E^2 = \frac {\sigma_y^2}{\sigma^2} = \frac {10}{2/3} \stackrel{!}{=}15,$$
$$\rho_{xy} = \frac{A \cdot D + B \cdot E}{\sqrt{(A^2 + B^2)(D^2 + E^2)}} = \frac{\sqrt{3} \cdot (D + E)}{\sqrt{6 \cdot (D^2 + E^2)}} \stackrel{!}{=} \sqrt{0.9}.$$
  • From this it further follows:  $D + E = \sqrt{1.8 \cdot ( D^2 + E^2)} = \sqrt{27} = 3 \cdot \sqrt{3}.$
  • The equation,  in conjunction with  $D^2 + E^2 = 15$  and the constraint  $(D>E)$  leads to the result:
$$ D= 2 \cdot \sqrt{3}\hspace{0.15cm}\underline{ = 3.464}, \hspace{0.5cm}E= \sqrt{3} \hspace{0.15cm}\underline{= 1.732}.$$


(4)  The random variables  $x$  and  $y$  resp. take their maximum values when  $u= +1$ and  $v= +1$  holds:

$$ x_\text{max}= A+B \hspace{0.15cm}\underline{ = +3.464}, \hspace{0.5cm} x_\text{min} = - A - B= -3.464.$$
$$ y_\text{max}= D+E+F \hspace{0.15cm}\underline{ = +6.196}, \hspace{0.5cm} y_\text{min} = -D-E+F= -4.196.$$