Weird Rice distribution
$begingroup$
In an old engineer online course (DNV Ocean), they derive the probability of local maxima of a joint gaussian process. From Equation 4.1.82:
$$
f(x,w) = frac{1}{(2pi)^{3/2}varepsilonsqrt{M_0M_2M_4}}e^{-frac{1}{(2varepsilon^2)}[x^2/M_0+2sqrt{1-varepsilon^2}frac{xw}{M_0M_4}+w^2/M_4]}.w
$$
and eluding the computation, they get the following expression of a (time localized) PDF:
$$
f(x) = frac{varepsilon}{sqrt{2pi}sigma}e^{-frac{1}{2}(frac{x}{varepsilonsigma})^2}+sqrt{1 - varepsilon^2} Phi(frac{sqrt{1 - varepsilon^2}}{varepsilon}frac{x}{sigma}) frac{x}{sigma^2} e^{-frac{1}{2}(frac{x}{sigma})^2}
$$
$Phi$ being the classical erf function.
And this is what they call Rice distribution. If I follow the reference therein, it brings me to the paper
D.E.Cartwright and M.S.Longuet-Higgins, "The Statistical Distribution of the Maximal of Random Functions." Royal Society of London. Proceedings Series A. 273, 212 (1956).
And in this one, they refer to an original book of Rice:
Rice, S. O. (1944). Mathematical analysis of random noise. Bell System Technical Journal, 23(3), 282-332.
which is also cited by the first page.
I am quite confused as I only know this form of the Rice distribution (formula taken from Wikipedia):
$$
f(xmid nu ,sigma )={frac {x}{sigma ^{2}}}exp left({frac {-(x^{2}+nu ^{2})}{2sigma ^{2}}}right)I_{0}left({frac {xnu }{sigma ^{2}}}right)
$$
And I think the two forms are far from equivalent... Am I right? Are there several "well-known" Rice distributions? Am I experiencing a change in terminology?
probability-distributions math-history
$endgroup$
add a comment |
$begingroup$
In an old engineer online course (DNV Ocean), they derive the probability of local maxima of a joint gaussian process. From Equation 4.1.82:
$$
f(x,w) = frac{1}{(2pi)^{3/2}varepsilonsqrt{M_0M_2M_4}}e^{-frac{1}{(2varepsilon^2)}[x^2/M_0+2sqrt{1-varepsilon^2}frac{xw}{M_0M_4}+w^2/M_4]}.w
$$
and eluding the computation, they get the following expression of a (time localized) PDF:
$$
f(x) = frac{varepsilon}{sqrt{2pi}sigma}e^{-frac{1}{2}(frac{x}{varepsilonsigma})^2}+sqrt{1 - varepsilon^2} Phi(frac{sqrt{1 - varepsilon^2}}{varepsilon}frac{x}{sigma}) frac{x}{sigma^2} e^{-frac{1}{2}(frac{x}{sigma})^2}
$$
$Phi$ being the classical erf function.
And this is what they call Rice distribution. If I follow the reference therein, it brings me to the paper
D.E.Cartwright and M.S.Longuet-Higgins, "The Statistical Distribution of the Maximal of Random Functions." Royal Society of London. Proceedings Series A. 273, 212 (1956).
And in this one, they refer to an original book of Rice:
Rice, S. O. (1944). Mathematical analysis of random noise. Bell System Technical Journal, 23(3), 282-332.
which is also cited by the first page.
I am quite confused as I only know this form of the Rice distribution (formula taken from Wikipedia):
$$
f(xmid nu ,sigma )={frac {x}{sigma ^{2}}}exp left({frac {-(x^{2}+nu ^{2})}{2sigma ^{2}}}right)I_{0}left({frac {xnu }{sigma ^{2}}}right)
$$
And I think the two forms are far from equivalent... Am I right? Are there several "well-known" Rice distributions? Am I experiencing a change in terminology?
probability-distributions math-history
$endgroup$
add a comment |
$begingroup$
In an old engineer online course (DNV Ocean), they derive the probability of local maxima of a joint gaussian process. From Equation 4.1.82:
$$
f(x,w) = frac{1}{(2pi)^{3/2}varepsilonsqrt{M_0M_2M_4}}e^{-frac{1}{(2varepsilon^2)}[x^2/M_0+2sqrt{1-varepsilon^2}frac{xw}{M_0M_4}+w^2/M_4]}.w
$$
and eluding the computation, they get the following expression of a (time localized) PDF:
$$
f(x) = frac{varepsilon}{sqrt{2pi}sigma}e^{-frac{1}{2}(frac{x}{varepsilonsigma})^2}+sqrt{1 - varepsilon^2} Phi(frac{sqrt{1 - varepsilon^2}}{varepsilon}frac{x}{sigma}) frac{x}{sigma^2} e^{-frac{1}{2}(frac{x}{sigma})^2}
$$
$Phi$ being the classical erf function.
And this is what they call Rice distribution. If I follow the reference therein, it brings me to the paper
D.E.Cartwright and M.S.Longuet-Higgins, "The Statistical Distribution of the Maximal of Random Functions." Royal Society of London. Proceedings Series A. 273, 212 (1956).
And in this one, they refer to an original book of Rice:
Rice, S. O. (1944). Mathematical analysis of random noise. Bell System Technical Journal, 23(3), 282-332.
which is also cited by the first page.
I am quite confused as I only know this form of the Rice distribution (formula taken from Wikipedia):
$$
f(xmid nu ,sigma )={frac {x}{sigma ^{2}}}exp left({frac {-(x^{2}+nu ^{2})}{2sigma ^{2}}}right)I_{0}left({frac {xnu }{sigma ^{2}}}right)
$$
And I think the two forms are far from equivalent... Am I right? Are there several "well-known" Rice distributions? Am I experiencing a change in terminology?
probability-distributions math-history
$endgroup$
In an old engineer online course (DNV Ocean), they derive the probability of local maxima of a joint gaussian process. From Equation 4.1.82:
$$
f(x,w) = frac{1}{(2pi)^{3/2}varepsilonsqrt{M_0M_2M_4}}e^{-frac{1}{(2varepsilon^2)}[x^2/M_0+2sqrt{1-varepsilon^2}frac{xw}{M_0M_4}+w^2/M_4]}.w
$$
and eluding the computation, they get the following expression of a (time localized) PDF:
$$
f(x) = frac{varepsilon}{sqrt{2pi}sigma}e^{-frac{1}{2}(frac{x}{varepsilonsigma})^2}+sqrt{1 - varepsilon^2} Phi(frac{sqrt{1 - varepsilon^2}}{varepsilon}frac{x}{sigma}) frac{x}{sigma^2} e^{-frac{1}{2}(frac{x}{sigma})^2}
$$
$Phi$ being the classical erf function.
And this is what they call Rice distribution. If I follow the reference therein, it brings me to the paper
D.E.Cartwright and M.S.Longuet-Higgins, "The Statistical Distribution of the Maximal of Random Functions." Royal Society of London. Proceedings Series A. 273, 212 (1956).
And in this one, they refer to an original book of Rice:
Rice, S. O. (1944). Mathematical analysis of random noise. Bell System Technical Journal, 23(3), 282-332.
which is also cited by the first page.
I am quite confused as I only know this form of the Rice distribution (formula taken from Wikipedia):
$$
f(xmid nu ,sigma )={frac {x}{sigma ^{2}}}exp left({frac {-(x^{2}+nu ^{2})}{2sigma ^{2}}}right)I_{0}left({frac {xnu }{sigma ^{2}}}right)
$$
And I think the two forms are far from equivalent... Am I right? Are there several "well-known" Rice distributions? Am I experiencing a change in terminology?
probability-distributions math-history
probability-distributions math-history
asked Dec 17 '18 at 14:55
Bentoy13Bentoy13
1063
1063
add a comment |
add a comment |
0
active
oldest
votes
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
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3044045%2fweird-rice-distribution%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
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.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3044045%2fweird-rice-distribution%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
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