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- [[Category:continuous random variable]] ...roblem]]: normalizing the probability mass function of a continuous random variable=2 KB (288 words) - 15:49, 22 March 2013
- #REDIRECT [[Practice Question uniform random variable mean ECE302S13Boutin]]76 B (10 words) - 07:33, 25 February 2013
- [[Category:continuous random variable]] ...roblem]]: normalizing the probability mass function of a continuous random variable=2 KB (401 words) - 04:52, 4 March 2013
- #REDIRECT [[Practice Question linear random variable probability ECE302S13Boutin]]82 B (10 words) - 07:43, 25 February 2013
Page text matches
- == Problem 1: Arbitrary Random Variables == Let <math>U</math> be a uniform random variable on [0,1].4 KB (596 words) - 12:57, 22 November 2011
- ...the function is a "non-decreasing function" and that U is a uniform random variable. This is enough information to make this step. So, ...x)) = F(x)\quad \text{(because }\Pr(U \leq y) = y,\text{ since }U\text{ is uniform on the unit interval)}862 B (156 words) - 05:42, 21 October 2008
- ...correct, I forgot the 2pi factor to change the range of the uniform random variable from [0-1] to [1-2pi].318 B (57 words) - 16:07, 21 October 2008
- OK, so what we have initially is a uniform random variable on the interval [0,1]. ...hat an exponential random variable with λ=0.5 is made out of two gaussian random variables with the relationship '''<math>D=X^2+Y^2</math>'''1 KB (186 words) - 11:47, 21 October 2008
- *(a) What is the maximum variance possible for a Bernoulli random variable? *(b) What is the maximum variance possible for a binomial random variable, with parameter <math>n = 1000</math>?3 KB (528 words) - 12:58, 22 November 2011
- The parameter of an exponential random variable has to be estimated from one sample. What is the ML estimator? Is it unbias == Problem 4: Uniform Parameter Estimation ==3 KB (500 words) - 12:50, 22 November 2011
- == Problem 1: Random Point, Revisited== In the following problems, the random point (X , Y) is uniformly distributed on the shaded region shown.4 KB (703 words) - 12:58, 22 November 2011
- *'''I. Guyon and A. Elisseeff, "An Introduction to Variable and Feature Selection", Journal of Machine Learning Research, vol. 3, pp.11 Variable and feature selection have become the focus of much research in areas of ap39 KB (5,715 words) - 10:52, 25 April 2008
- ...{-j\nu}). Use the fact that the sequence was derived from a uniform random variable. The link below (from wikipedia) is useful to get the info you need from th ...ndering if its ok to use randn instead when we want to generate the random variable between -0.5 and 0.5...2 KB (258 words) - 00:51, 22 March 2008
- ...d-inline-policy: -moz-initial;" colspan="2" | Expectation and Variance of Random Variables | align="right" style="padding-right: 1em;" | Binomial random variable with parameters n and p3 KB (491 words) - 12:54, 3 March 2015
- | Random variable | Uniform <math> U(a,b) </math>6 KB (851 words) - 15:34, 23 April 2013
- [[Category:continuous random variable]] [[Category:uniform random variable]]2 KB (284 words) - 11:49, 26 March 2013
- [[Category:continuous random variable]] [[Category:uniform random variable]]1 KB (157 words) - 11:59, 26 March 2013
- [[Category:continuous random variable]] [[Category:uniform random variable]]1,022 B (148 words) - 12:00, 26 March 2013
- ...nal density when the condition is an event B (instead of the event "random variable Y=y").3 KB (350 words) - 11:24, 6 March 2013
- *[[Practice Question uniform random variable mean ECE302S13Boutin|Laroche - Compute the mean]] ...302S13Boutin|Kecheng/li485 - Compute first order moment of Gaussian random variable]]2 KB (232 words) - 10:56, 14 April 2013
- ...{-j\nu}). Use the fact that the sequence was derived from a uniform random variable. The link below (from wikipedia) is useful to get the info you need from th ...ndering if its ok to use randn instead when we want to generate the random variable between -0.5 and 0.5...2 KB (264 words) - 08:05, 9 April 2013
- [[ECE600_F13_rv_definition_mhossain|Previous Topic: Random Variables: Definitions]]<br/> [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']]15 KB (2,637 words) - 12:11, 21 May 2014
- ...unctions_of_random_variable_mhossain|Previous Topic: Functions of a Random Variable]]<br/> [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']]8 KB (1,474 words) - 12:12, 21 May 2014
- [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] <font size= 3> Topic 16: Conditional Expectation for Two Random Variables</font size>4 KB (875 words) - 12:13, 21 May 2014
- <font size="4">Question 1: Probability and Random Processes </font> ...f{X}_{n} \dots </math> be a sequence of independent, identical distributed random variables, each uniformly distributed on the interval [0, 1], an hence havi12 KB (1,948 words) - 10:16, 15 August 2014
- ...cess. A stochastic process { X(t), t∈T } is an ordered collection of random variables, T where T is the index set and if t is a time in the set, X(t) i ...h models that use X1,…,Xn as independently identically distributed (iid) random variables. However, note that states do not necessarily have to be independ19 KB (3,004 words) - 09:39, 23 April 2014
- ...nd way was using a uniform random variable in vector operations. A uniform random vector of the same size of the whole dataset is first generated, whose each ...ld be easy to understand even for people who do not have deep knowledge in random variables & probabilities. The demonstrations (figures & codes) in MATLAB w3 KB (508 words) - 16:12, 14 May 2014
- ...ven value of θ is denoted by p(x|θ ). It should be noted that the random variable X and the parameter θ can be vector-valued. Now we obtain a set of indepen ...s parameter estimation, the parameter θ is viewed as a random variable or random vector following the distribution p(θ ). Then the probability density func15 KB (2,273 words) - 10:51, 22 January 2015
- ...Geometric Distribution, Binomial Distribution, Poisson Distribution, and Uniform Distribution ** Uniform Distribution12 KB (1,986 words) - 10:49, 22 January 2015
