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- ...binomial distribution and make n large and p small, do you get the poisson distribution ?)326 B (57 words) - 08:07, 12 September 2008
- ...Binomial and Poisson Distributions_Old Kiwi|Examples of MLE: Binomial and Poisson Distributions]] ...Binomial and Poisson Distributions_Old Kiwi|Examples of MLE: Binomial and Poisson Distributions]]10 KB (1,488 words) - 10:16, 20 May 2013
- [[Category:exponential distribution]] [[Category:geometric distribution]]3 KB (498 words) - 10:13, 20 May 2013
- [[Category:binomial distribution]] [[Category:poisson distribution]]2 KB (366 words) - 10:14, 20 May 2013
- ...pics Covered''': An introductory treatment of probability theory including distribution and density functions, moments and random variables. Applications of normal <br/><br/>3. Independence, Cumulative Distribution Function (used in ECE 438), Probability Density Function (used in ECE 438),2 KB (231 words) - 07:20, 4 May 2010
- *[[Probability_Distribution|Probability Distribution]] ...on_of_two_independent_Poisson_random_variables|Addition of two independent Poisson random variables]]2 KB (238 words) - 12:14, 25 September 2013
- =Addition of two independent Poisson random variables = ...where <math>\mathbf{X}</math> and <math>\mathbf{Y}</math> are independent Poisson random variables with means <math>\lambda</math> and <math>\mu</math>, resp3 KB (557 words) - 12:11, 25 September 2013
- *[[ECE 600 Prerequisites Poisson Random Process|Poisson Random Process]] ...tribution Function) and PDF (Probability Density Function)|CDF (Cumulative Distribution Function) and PDF (Probability Density Function)]]1 KB (139 words) - 13:13, 16 November 2010
- ='''1.4.1 Bernoulli distribution'''= ='''1.4.2 Binomial distribution'''=5 KB (921 words) - 11:25, 30 November 2010
- ='''1.5 Poisson Process'''= ...f{N}\left(t\right),\; t\geq0\right\}</math> is the Poinsson process. The distribution of <math class="inline">\mathbf{N}\left(t\right)</math> is gained by inser5 KB (920 words) - 11:26, 30 November 2010
- '''1.6.1 Gaussian distribution (normal distribution)''' <math class="inline">\mathcal{N}\left(\mu,\sigma^{2}\right)</math> '''1.6.2 Log-normal distribution <math class="inline">\ln\mathcal{N}\left(\mu,\sigma^{2}\right)</math>'''5 KB (843 words) - 11:27, 30 November 2010
- ...er of hits <math class="inline">\mathbf{X}</math> in a baseball game is a Poisson random variable. If the probability of a no-hit game is 1/3 , what is the p ...athbf{Y}\left(t_{1}\right),\mathbf{Y}\left(t_{2}\right)\right)</math> has distribution <math class="inline">N\left[0,0,N_{0}T,N_{0}T,1-\frac{\left|\tau\right|}{T}12 KB (2,205 words) - 07:20, 1 December 2010
- ...the origin (the lower left corner of the unit square). Find the cumulative distribution function (cdf) <math class="inline">F_{\mathbf{X}}\left(x\right)=P\left(\le ...stars within a galaxy is accurately modeled by a 3-dimensional homogeneous Poisson process for which the following two facts are known to be true:10 KB (1,652 words) - 08:32, 27 June 2012
- ...applied to <math class="inline">\mathbf{Y}</math> will yield the desired distribution for <math class="inline">\mathbf{X}</math> ? Prove your answer. ...at the origin. You must quote, but do not have to prove, properties of the Poisson process that you use in your solutions to the following questions:10 KB (1,608 words) - 08:31, 27 June 2012
- ...except that it deals with the exponential random variable rather than the Poisson random variable. ...ion of the [[ECE 600 Prerequisites Continuous Random Variables|exponential distribution]], <math class="inline">f_{\mathbf{X}}\left(x\right)=\frac{1}{\mu}e^{-\frac14 KB (2,358 words) - 08:31, 27 June 2012
- ...X}_{2},\cdots,\mathbf{X}_{n},\cdots</math> converges in distribution to a Poisson random variable having mean <math class="inline">\lambda</math> . ...<math class="inline">\mathbf{X}_{n}</math> converges in distribution to a Poisson random variable with mean <math class="inline">\lambda</math> .10 KB (1,754 words) - 08:30, 27 June 2012
- ...telephone towers can be accurately modeled by a 2-dimensional homogeneous Poisson process for which the following two facts are know to be true: 1. The number of towers in a region of area A is a Poisson random variable with mean \lambda A , where \lambda>0 .9 KB (1,560 words) - 08:30, 27 June 2012
- ...\{ \mathbf{X}_{n}\right\} _{n\geq1}</math> converges in distribution to a Poisson random variable <math class="inline">\mathbf{X}</math> with mean <math cla ...mathbf{Y}_{3},\cdots</math> converge in distribution? If yes, what is the distribution of the random variable it converges to?10 KB (1,636 words) - 08:29, 27 June 2012
- =Example. Addition of two independent Poisson random variables= ...hbf{X}</math> and <math class="inline">\mathbf{Y}</math> are independent Poisson random variables with means <math class="inline">\lambda</math> and <math3 KB (532 words) - 11:58, 30 November 2010
- ...\{ \mathbf{X}_{n}\right\} _{n\leq1}</math> converges in distribution to a Poisson random variable <math>\mathbf{X}</math> with mean <math>\lambda</math> . ...math>n\rightarrow\infty</math> , which is the characteristic function of a Poisson random variable with mean <math>\lambda</math> .3 KB (470 words) - 13:02, 23 November 2010
- ...\{ \mathbf{X}_{n}\right\} _{n\leq1}</math> converges in distribution to a Poisson random variable <math class="inline">\mathbf{X}</math> with mean <math cla ...ine">n\rightarrow\infty</math> , which is the characteristic function of a Poisson random variable with mean <math class="inline">\lambda</math> .3 KB (539 words) - 12:14, 30 November 2010
- | <math> F- </math> distribution | Poisson <math> P(\lambda) </math>6 KB (851 words) - 15:34, 23 April 2013
- ...Binomial and Poisson Distributions_Old Kiwi|Examples of MLE: Binomial and Poisson Distributions]] ...es: Binomial and Poisson Distributions_OldKiwi|[MLE Examples: Binomial and Poisson Distributions]]10 KB (1,472 words) - 11:16, 10 June 2013
- ...we talked about Maximum Likelihood Estimation (MLE) of the parameters of a distribution. ...ples:_Binomial_and_Poisson_Distributions_OldKiwi|MLE example: binomial and poisson distributions]]2 KB (196 words) - 09:54, 23 April 2012
- =Maximum Likelihood Estimation (MLE) example: Bernouilli Distribution= === Poisson Distribution ===2 KB (310 words) - 09:58, 23 April 2012
- ...s: [[MLE_Examples:_Binomial_and_Poisson_Distributions_OldKiwi|Binomial and Poisson distributions]] '''Exponential Distribution'''3 KB (446 words) - 10:00, 23 April 2012
- ...\{ \mathbf{X}_{n}\right\} _{n\geq1}</math> converges in distribution to a Poisson random variable <math class="inline">\mathbf{X}</math> with mean <math cla ...mathbf{Y}_{3},\cdots</math> converge in distribution? If yes, what is the distribution of the random variable it converges to?5 KB (763 words) - 10:57, 10 March 2015
- ...the origin (the lower left corner of the unit square). Find the cumulative distribution function (cdf) <math class="inline">F_{\mathbf{X}}\left(x\right)=P\left(\le ...stars within a galaxy is accurately modeled by a 3-dimensional homogeneous Poisson process for which the following two facts are known to be true:5 KB (766 words) - 00:16, 10 March 2015
- ...applied to <math class="inline">\mathbf{Y}</math> will yield the desired distribution for <math class="inline">\mathbf{X}</math> ? Prove your answer. ...at the origin. You must quote, but do not have to prove, properties of the Poisson process that you use in your solutions to the following questions:5 KB (729 words) - 00:51, 10 March 2015
- ...X}_{2},\cdots,\mathbf{X}_{n},\cdots</math> converges in distribution to a Poisson random variable having mean <math class="inline">\lambda</math> . Consider a homogeneous Poisson point process with rate <math class="inline">\lambda</math> and points (ev4 KB (609 words) - 01:54, 10 March 2015
- *3.3 The cumulative distribution function of a random variable (discrete or continuous) *4.4 The Poisson Random Process and its relationship to Binomial Counting4 KB (498 words) - 10:18, 17 April 2013
- '''Applications of Poisson Random Variables''' == Poisson Random Variables==5 KB (708 words) - 07:22, 22 April 2013
- # the cumulative distribution function (cdf) '''Definition''' <math>\quad</math> The '''cumulative distribution function (cdf)''' of X is defined as <br/>15 KB (2,637 words) - 12:11, 21 May 2014
- ...c Distribution, Binomial Distribution, Poisson Distribution, and Uniform Distribution ** Exponential Distribution12 KB (1,986 words) - 10:49, 22 January 2015
- In the circumstance, a naive assumption about the class distribution helps us synthesize data so that we can train models with a consistent data Among many distributions, Normal distribution is frequently used in many literatures.16 KB (2,400 words) - 23:34, 29 April 2014
- ...n train models with a consistent dataset. Among many distributions, Normal distribution is frequently used in many literatures. This tutorial will explain how to g # Normal distribution : How it work? Which is more efficient?18 KB (2,852 words) - 10:40, 22 January 2015
- ...ity distribution, MLE provides the estimates for the parameters of density distribution model. In real estimation, we search over all the possible sets of paramete ...o use MLE is to find the vector of parameters that is as close to the true distribution parameter value as possible.<br>13 KB (1,966 words) - 10:50, 22 January 2015
- ...stars within a galaxy is accurately modeled by a 3-dimensional homogeneous Poisson process for which the following two facts are known to be true: ...number of starts in a region of volume <math class="inline">V</math> is a Poisson random variable with mean <math class="inline">\lambda V</math> , where <ma2 KB (384 words) - 00:22, 10 March 2015
- ...at the origin. You must quote, but do not have to prove, properties of the Poisson process that you use in your solutions to the following questions: Given that a node is in the circle C , determine the density or distribution function of its distance <math class="inline">\mathbf{D}</math> from the o3 KB (414 words) - 00:55, 10 March 2015
- ...except that it deals with the exponential random variable rather than the Poisson random variable. ...ion of the [[ECE 600 Prerequisites Continuous Random Variables|exponential distribution]], <math class="inline">f_{\mathbf{X}}\left(x\right)=\frac{1}{\mu}e^{-\frac2 KB (366 words) - 01:36, 10 March 2015
- ...X}_{2},\cdots,\mathbf{X}_{n},\cdots</math> converges in distribution to a Poisson random variable having mean <math class="inline">\lambda</math> . ...<math class="inline">\mathbf{X}_{n}</math> converges in distribution to a Poisson random variable with mean <math class="inline">\lambda</math> .3 KB (429 words) - 01:57, 10 March 2015
- Consider a homogeneous Poisson point process with rate <math class="inline">\lambda</math> and points (ev – This is Erlang distribution.4 KB (679 words) - 01:58, 10 March 2015
- ...telephone towers can be accurately modeled by a 2-dimensional homogeneous Poisson process for which the following two facts are know to be true: 1. The number of towers in a region of area A is a Poisson random variable with mean \lambda A , where \lambda>0 .4 KB (646 words) - 10:26, 10 March 2015
- ...\{ \mathbf{X}_{n}\right\} _{n\geq1}</math> converges in distribution to a Poisson random variable <math class="inline">\mathbf{X}</math> with mean <math cla2 KB (258 words) - 10:58, 10 March 2015
- First of all, the conditional distribution can be written as: ...through the lens of Bayes' Theorem. As such, we can write the conditional distribution as4 KB (851 words) - 23:04, 31 January 2016
- ...style="color:green"> Lack of proof. Should mention the property of Poisson distribution to show the equivalence. See the proof in solution 2.</span> ...k!}</math> is a Potion distribution, it is known that the expectation of a Poisson RV is <math>\lambda_x</math>.3 KB (529 words) - 16:42, 18 May 2017
- '''(a)''' Find the cumulative distribution function (cdf) of <math>\mathbf{X}</math>.<br> '''(b)''' Find the probability distribution function (pdf) of <math>\mathbf{X}</math>.<br>3 KB (502 words) - 15:33, 19 February 2019
- ...ce of how <math>e</math> relates to probability, specifically the binomial distribution. Now, we will consider its relationship with derangements and will explain This now demonstrates how, just as with the Binomial Distribution, <math>e</math> appears in relatively unexpected locations, and now that we6 KB (996 words) - 00:53, 3 December 2018
- ...Processes with rate <math>\lambda</math>. Assume that <math>K</math> is a Poisson random variable independent of <math>N_{i}(t)</math> (for all i) and has me i.(5 points) Statement: <math>\{ N(t), t \geq 0 \}</math> is a Poisson process with rate <math>a \lambda</math>. <br/>5 KB (910 words) - 03:02, 24 February 2019
