PDF of an exponential distribution with varying paramter, lambda












1














Suppose that the lifetime of a device is exponential with rate λ, but suppose
also that the value of λ is not fixed but is itself a random variable that is
uniform in the range [a, b) with 0 < a.



Can the pdf of the lifetime of the device be written as:



$ lambda = begin{cases} 0, x < a\ dfrac {1} {b-a} , aleq x < b\ 0, xgeq b end{cases} $










share|cite|improve this question




















  • 1




    The PDF of $lambda$, or the PDF of the lifetime of the device?
    – Clarinetist
    Nov 30 at 1:12










  • If $lambda$ is Uniform on $[a,b)$, then the PDF would be 0 for $xgeq b$.
    – gd1035
    Nov 30 at 1:18










  • What you wrote is the PDF of the random variable $lambda$, not the PDF of the device lifetime.
    – BlackMath
    Nov 30 at 6:06


















1














Suppose that the lifetime of a device is exponential with rate λ, but suppose
also that the value of λ is not fixed but is itself a random variable that is
uniform in the range [a, b) with 0 < a.



Can the pdf of the lifetime of the device be written as:



$ lambda = begin{cases} 0, x < a\ dfrac {1} {b-a} , aleq x < b\ 0, xgeq b end{cases} $










share|cite|improve this question




















  • 1




    The PDF of $lambda$, or the PDF of the lifetime of the device?
    – Clarinetist
    Nov 30 at 1:12










  • If $lambda$ is Uniform on $[a,b)$, then the PDF would be 0 for $xgeq b$.
    – gd1035
    Nov 30 at 1:18










  • What you wrote is the PDF of the random variable $lambda$, not the PDF of the device lifetime.
    – BlackMath
    Nov 30 at 6:06
















1












1








1







Suppose that the lifetime of a device is exponential with rate λ, but suppose
also that the value of λ is not fixed but is itself a random variable that is
uniform in the range [a, b) with 0 < a.



Can the pdf of the lifetime of the device be written as:



$ lambda = begin{cases} 0, x < a\ dfrac {1} {b-a} , aleq x < b\ 0, xgeq b end{cases} $










share|cite|improve this question















Suppose that the lifetime of a device is exponential with rate λ, but suppose
also that the value of λ is not fixed but is itself a random variable that is
uniform in the range [a, b) with 0 < a.



Can the pdf of the lifetime of the device be written as:



$ lambda = begin{cases} 0, x < a\ dfrac {1} {b-a} , aleq x < b\ 0, xgeq b end{cases} $







probability uniform-distribution exponential-distribution






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Nov 30 at 1:25

























asked Nov 30 at 1:11









Basileus

113




113








  • 1




    The PDF of $lambda$, or the PDF of the lifetime of the device?
    – Clarinetist
    Nov 30 at 1:12










  • If $lambda$ is Uniform on $[a,b)$, then the PDF would be 0 for $xgeq b$.
    – gd1035
    Nov 30 at 1:18










  • What you wrote is the PDF of the random variable $lambda$, not the PDF of the device lifetime.
    – BlackMath
    Nov 30 at 6:06
















  • 1




    The PDF of $lambda$, or the PDF of the lifetime of the device?
    – Clarinetist
    Nov 30 at 1:12










  • If $lambda$ is Uniform on $[a,b)$, then the PDF would be 0 for $xgeq b$.
    – gd1035
    Nov 30 at 1:18










  • What you wrote is the PDF of the random variable $lambda$, not the PDF of the device lifetime.
    – BlackMath
    Nov 30 at 6:06










1




1




The PDF of $lambda$, or the PDF of the lifetime of the device?
– Clarinetist
Nov 30 at 1:12




The PDF of $lambda$, or the PDF of the lifetime of the device?
– Clarinetist
Nov 30 at 1:12












If $lambda$ is Uniform on $[a,b)$, then the PDF would be 0 for $xgeq b$.
– gd1035
Nov 30 at 1:18




If $lambda$ is Uniform on $[a,b)$, then the PDF would be 0 for $xgeq b$.
– gd1035
Nov 30 at 1:18












What you wrote is the PDF of the random variable $lambda$, not the PDF of the device lifetime.
– BlackMath
Nov 30 at 6:06






What you wrote is the PDF of the random variable $lambda$, not the PDF of the device lifetime.
– BlackMath
Nov 30 at 6:06












1 Answer
1






active

oldest

votes


















1














Let $T|lambda sim text{Exp}(lambda)$ be the lifetime of the device and let $lambda sim text{U}[a,b)$ be the parameter. Then for all $t geqslant 0$ you have:



$$begin{equation} begin{aligned}
f_T(t)
&= int limits_a^b p(T=t|lambda) pi(lambda) dlambda \[6pt]
&= frac{1}{a-b} int limits_a^b exp(-lambda t) dlambda \[6pt]
&= frac{1}{a-b} Bigg[ - frac{1}{t} cdot exp(-lambda t) Bigg]_{lambda=a}^{lambda=b} \[6pt]
&= frac{1}{a-b} Bigg[ frac{exp(-at) - exp(-bt)}{t} Bigg] \[6pt]
&= frac{e^{-at} - e^{-bt}}{a-b} cdot frac{1}{t}. \[6pt]
end{aligned} end{equation}$$






share|cite|improve this answer





















  • So, this has to take into account the law of total probability, thanks for that.
    – Basileus
    Nov 30 at 13:09










  • Yes, the first step is an application of that law.
    – Ben
    Nov 30 at 22:51











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%2f3019485%2fpdf-of-an-exponential-distribution-with-varying-paramter-lambda%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









1














Let $T|lambda sim text{Exp}(lambda)$ be the lifetime of the device and let $lambda sim text{U}[a,b)$ be the parameter. Then for all $t geqslant 0$ you have:



$$begin{equation} begin{aligned}
f_T(t)
&= int limits_a^b p(T=t|lambda) pi(lambda) dlambda \[6pt]
&= frac{1}{a-b} int limits_a^b exp(-lambda t) dlambda \[6pt]
&= frac{1}{a-b} Bigg[ - frac{1}{t} cdot exp(-lambda t) Bigg]_{lambda=a}^{lambda=b} \[6pt]
&= frac{1}{a-b} Bigg[ frac{exp(-at) - exp(-bt)}{t} Bigg] \[6pt]
&= frac{e^{-at} - e^{-bt}}{a-b} cdot frac{1}{t}. \[6pt]
end{aligned} end{equation}$$






share|cite|improve this answer





















  • So, this has to take into account the law of total probability, thanks for that.
    – Basileus
    Nov 30 at 13:09










  • Yes, the first step is an application of that law.
    – Ben
    Nov 30 at 22:51
















1














Let $T|lambda sim text{Exp}(lambda)$ be the lifetime of the device and let $lambda sim text{U}[a,b)$ be the parameter. Then for all $t geqslant 0$ you have:



$$begin{equation} begin{aligned}
f_T(t)
&= int limits_a^b p(T=t|lambda) pi(lambda) dlambda \[6pt]
&= frac{1}{a-b} int limits_a^b exp(-lambda t) dlambda \[6pt]
&= frac{1}{a-b} Bigg[ - frac{1}{t} cdot exp(-lambda t) Bigg]_{lambda=a}^{lambda=b} \[6pt]
&= frac{1}{a-b} Bigg[ frac{exp(-at) - exp(-bt)}{t} Bigg] \[6pt]
&= frac{e^{-at} - e^{-bt}}{a-b} cdot frac{1}{t}. \[6pt]
end{aligned} end{equation}$$






share|cite|improve this answer





















  • So, this has to take into account the law of total probability, thanks for that.
    – Basileus
    Nov 30 at 13:09










  • Yes, the first step is an application of that law.
    – Ben
    Nov 30 at 22:51














1












1








1






Let $T|lambda sim text{Exp}(lambda)$ be the lifetime of the device and let $lambda sim text{U}[a,b)$ be the parameter. Then for all $t geqslant 0$ you have:



$$begin{equation} begin{aligned}
f_T(t)
&= int limits_a^b p(T=t|lambda) pi(lambda) dlambda \[6pt]
&= frac{1}{a-b} int limits_a^b exp(-lambda t) dlambda \[6pt]
&= frac{1}{a-b} Bigg[ - frac{1}{t} cdot exp(-lambda t) Bigg]_{lambda=a}^{lambda=b} \[6pt]
&= frac{1}{a-b} Bigg[ frac{exp(-at) - exp(-bt)}{t} Bigg] \[6pt]
&= frac{e^{-at} - e^{-bt}}{a-b} cdot frac{1}{t}. \[6pt]
end{aligned} end{equation}$$






share|cite|improve this answer












Let $T|lambda sim text{Exp}(lambda)$ be the lifetime of the device and let $lambda sim text{U}[a,b)$ be the parameter. Then for all $t geqslant 0$ you have:



$$begin{equation} begin{aligned}
f_T(t)
&= int limits_a^b p(T=t|lambda) pi(lambda) dlambda \[6pt]
&= frac{1}{a-b} int limits_a^b exp(-lambda t) dlambda \[6pt]
&= frac{1}{a-b} Bigg[ - frac{1}{t} cdot exp(-lambda t) Bigg]_{lambda=a}^{lambda=b} \[6pt]
&= frac{1}{a-b} Bigg[ frac{exp(-at) - exp(-bt)}{t} Bigg] \[6pt]
&= frac{e^{-at} - e^{-bt}}{a-b} cdot frac{1}{t}. \[6pt]
end{aligned} end{equation}$$







share|cite|improve this answer












share|cite|improve this answer



share|cite|improve this answer










answered Nov 30 at 5:45









Ben

92611




92611












  • So, this has to take into account the law of total probability, thanks for that.
    – Basileus
    Nov 30 at 13:09










  • Yes, the first step is an application of that law.
    – Ben
    Nov 30 at 22:51


















  • So, this has to take into account the law of total probability, thanks for that.
    – Basileus
    Nov 30 at 13:09










  • Yes, the first step is an application of that law.
    – Ben
    Nov 30 at 22:51
















So, this has to take into account the law of total probability, thanks for that.
– Basileus
Nov 30 at 13:09




So, this has to take into account the law of total probability, thanks for that.
– Basileus
Nov 30 at 13:09












Yes, the first step is an application of that law.
– Ben
Nov 30 at 22:51




Yes, the first step is an application of that law.
– Ben
Nov 30 at 22:51


















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.





Some of your past answers have not been well-received, and you're in danger of being blocked from answering.


Please pay close attention to the following guidance:


  • 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.


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%2f3019485%2fpdf-of-an-exponential-distribution-with-varying-paramter-lambda%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

To store a contact into the json file from server.js file using a class in NodeJS

Redirect URL with Chrome Remote Debugging Android Devices

Dieringhausen