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sum of two independent exponential distributions?
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)Product of exponential distributionsCompute $E(Xmid X+Y)$ for independent random variables $X$ and $Y$ with standard exponential distributionsSum of two independent, continuous random variablesanother follow up question: modeling with exponential distributionsSummed probability of two independent continuous random variables, limits$P(X_1 < X_2 < X_3)$ for Exponential Random VariablesDivision of Two exponential Random variablesFrom Exponential Distributions to Weibull Distribution (CDF)Poisson Process interpretationProbability of (exponential) arrival in between two (exponential) events
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The sum of two independent exponential distributions begin{aligned}{Z=omega_{1}X_{1}+omega_{2}X_{2}}end{aligned} is as follows.
begin{aligned}f_{Z}(z)=&int _{0}^{z}omega_{1}omega_{2}f_{X_{1}}(x_{1})f_{X_{2}}(z-x_{1}),dx_{1}\=omega_{1}omega_{2}&lambda _{1}lambda _{2}exp[-lambda _{2}z]int _{0}^{z}exp[(lambda _{2}-lambda _{1})x_{1}],dx_{1}\=&{frac {omega_{1}omega_{2}lambda _{1}lambda _{2}}{lambda _{2}-lambda _{1}}}left(exp[-lambda _{1}z]-exp[-lambda _{2}z]right)end{aligned}
But the following example doesn't follow the above equation.
begin{aligned}omega_1=exp(-0.114989504)end{aligned}
begin{aligned}omega_2=exp(-7.5448246293224)end{aligned}
begin{aligned}lambda_1=1/(4.3258*10^{-08})end{aligned}
begin{aligned}lambda_1=1/(1.8737*10^{-03})end{aligned}
The result is compared with conv(fX1,fX2)*(x_interval) in Matlab.
Can you tell me what the problem is?
probability exponential-distribution
$endgroup$
add a comment |
$begingroup$
The sum of two independent exponential distributions begin{aligned}{Z=omega_{1}X_{1}+omega_{2}X_{2}}end{aligned} is as follows.
begin{aligned}f_{Z}(z)=&int _{0}^{z}omega_{1}omega_{2}f_{X_{1}}(x_{1})f_{X_{2}}(z-x_{1}),dx_{1}\=omega_{1}omega_{2}&lambda _{1}lambda _{2}exp[-lambda _{2}z]int _{0}^{z}exp[(lambda _{2}-lambda _{1})x_{1}],dx_{1}\=&{frac {omega_{1}omega_{2}lambda _{1}lambda _{2}}{lambda _{2}-lambda _{1}}}left(exp[-lambda _{1}z]-exp[-lambda _{2}z]right)end{aligned}
But the following example doesn't follow the above equation.
begin{aligned}omega_1=exp(-0.114989504)end{aligned}
begin{aligned}omega_2=exp(-7.5448246293224)end{aligned}
begin{aligned}lambda_1=1/(4.3258*10^{-08})end{aligned}
begin{aligned}lambda_1=1/(1.8737*10^{-03})end{aligned}
The result is compared with conv(fX1,fX2)*(x_interval) in Matlab.
Can you tell me what the problem is?
probability exponential-distribution
$endgroup$
$begingroup$
The convolution in Matlab is a summation, not an integral. My guess is that you reached limits of numerical integration.
$endgroup$
– P. Quinton
Mar 23 at 12:47
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I reduced the x_interval for the convolution. And I solve that problem. Thank you so much.
$endgroup$
– kwonhj
Mar 23 at 12:55
$begingroup$
It's not really about the interval, it's more about the fact that sometimes $sum_n f(nDelta) Delta$ may not converge to $int f(x) dx$ when $Delta$ goes to $0$
$endgroup$
– P. Quinton
Mar 23 at 12:58
add a comment |
$begingroup$
The sum of two independent exponential distributions begin{aligned}{Z=omega_{1}X_{1}+omega_{2}X_{2}}end{aligned} is as follows.
begin{aligned}f_{Z}(z)=&int _{0}^{z}omega_{1}omega_{2}f_{X_{1}}(x_{1})f_{X_{2}}(z-x_{1}),dx_{1}\=omega_{1}omega_{2}&lambda _{1}lambda _{2}exp[-lambda _{2}z]int _{0}^{z}exp[(lambda _{2}-lambda _{1})x_{1}],dx_{1}\=&{frac {omega_{1}omega_{2}lambda _{1}lambda _{2}}{lambda _{2}-lambda _{1}}}left(exp[-lambda _{1}z]-exp[-lambda _{2}z]right)end{aligned}
But the following example doesn't follow the above equation.
begin{aligned}omega_1=exp(-0.114989504)end{aligned}
begin{aligned}omega_2=exp(-7.5448246293224)end{aligned}
begin{aligned}lambda_1=1/(4.3258*10^{-08})end{aligned}
begin{aligned}lambda_1=1/(1.8737*10^{-03})end{aligned}
The result is compared with conv(fX1,fX2)*(x_interval) in Matlab.
Can you tell me what the problem is?
probability exponential-distribution
$endgroup$
The sum of two independent exponential distributions begin{aligned}{Z=omega_{1}X_{1}+omega_{2}X_{2}}end{aligned} is as follows.
begin{aligned}f_{Z}(z)=&int _{0}^{z}omega_{1}omega_{2}f_{X_{1}}(x_{1})f_{X_{2}}(z-x_{1}),dx_{1}\=omega_{1}omega_{2}&lambda _{1}lambda _{2}exp[-lambda _{2}z]int _{0}^{z}exp[(lambda _{2}-lambda _{1})x_{1}],dx_{1}\=&{frac {omega_{1}omega_{2}lambda _{1}lambda _{2}}{lambda _{2}-lambda _{1}}}left(exp[-lambda _{1}z]-exp[-lambda _{2}z]right)end{aligned}
But the following example doesn't follow the above equation.
begin{aligned}omega_1=exp(-0.114989504)end{aligned}
begin{aligned}omega_2=exp(-7.5448246293224)end{aligned}
begin{aligned}lambda_1=1/(4.3258*10^{-08})end{aligned}
begin{aligned}lambda_1=1/(1.8737*10^{-03})end{aligned}
The result is compared with conv(fX1,fX2)*(x_interval) in Matlab.
Can you tell me what the problem is?
probability exponential-distribution
probability exponential-distribution
asked Mar 23 at 12:41
kwonhjkwonhj
11
11
$begingroup$
The convolution in Matlab is a summation, not an integral. My guess is that you reached limits of numerical integration.
$endgroup$
– P. Quinton
Mar 23 at 12:47
$begingroup$
I reduced the x_interval for the convolution. And I solve that problem. Thank you so much.
$endgroup$
– kwonhj
Mar 23 at 12:55
$begingroup$
It's not really about the interval, it's more about the fact that sometimes $sum_n f(nDelta) Delta$ may not converge to $int f(x) dx$ when $Delta$ goes to $0$
$endgroup$
– P. Quinton
Mar 23 at 12:58
add a comment |
$begingroup$
The convolution in Matlab is a summation, not an integral. My guess is that you reached limits of numerical integration.
$endgroup$
– P. Quinton
Mar 23 at 12:47
$begingroup$
I reduced the x_interval for the convolution. And I solve that problem. Thank you so much.
$endgroup$
– kwonhj
Mar 23 at 12:55
$begingroup$
It's not really about the interval, it's more about the fact that sometimes $sum_n f(nDelta) Delta$ may not converge to $int f(x) dx$ when $Delta$ goes to $0$
$endgroup$
– P. Quinton
Mar 23 at 12:58
$begingroup$
The convolution in Matlab is a summation, not an integral. My guess is that you reached limits of numerical integration.
$endgroup$
– P. Quinton
Mar 23 at 12:47
$begingroup$
The convolution in Matlab is a summation, not an integral. My guess is that you reached limits of numerical integration.
$endgroup$
– P. Quinton
Mar 23 at 12:47
$begingroup$
I reduced the x_interval for the convolution. And I solve that problem. Thank you so much.
$endgroup$
– kwonhj
Mar 23 at 12:55
$begingroup$
I reduced the x_interval for the convolution. And I solve that problem. Thank you so much.
$endgroup$
– kwonhj
Mar 23 at 12:55
$begingroup$
It's not really about the interval, it's more about the fact that sometimes $sum_n f(nDelta) Delta$ may not converge to $int f(x) dx$ when $Delta$ goes to $0$
$endgroup$
– P. Quinton
Mar 23 at 12:58
$begingroup$
It's not really about the interval, it's more about the fact that sometimes $sum_n f(nDelta) Delta$ may not converge to $int f(x) dx$ when $Delta$ goes to $0$
$endgroup$
– P. Quinton
Mar 23 at 12:58
add a comment |
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$begingroup$
The convolution in Matlab is a summation, not an integral. My guess is that you reached limits of numerical integration.
$endgroup$
– P. Quinton
Mar 23 at 12:47
$begingroup$
I reduced the x_interval for the convolution. And I solve that problem. Thank you so much.
$endgroup$
– kwonhj
Mar 23 at 12:55
$begingroup$
It's not really about the interval, it's more about the fact that sometimes $sum_n f(nDelta) Delta$ may not converge to $int f(x) dx$ when $Delta$ goes to $0$
$endgroup$
– P. Quinton
Mar 23 at 12:58