two-poisson model (2p)
1Poisson regression — In statistics, Poisson regression is a form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can …
2model — 1. A representation of something, often idealized or modified to make it conceptually easier to understand. 2. Something to be imitated. 3. In dentistry, a cast. 4. A mathematical representation of a particular phenomenon. 5. An animal that is… …
3Conway–Maxwell–Poisson distribution — Conway–Maxwell–Poisson parameters: support: pmf: cdf …
4Conway-Maxwell-Poisson distribution — Probability distribution name =Conway Maxwell Poisson pdf cdf type =density parameters =lambda > 0, u geq 0 support =x in {0,1,2,dots} pdf =frac{lambda^x}{(x!)^ u}frac{1}{Z(lambda, u)} cdf =sum {i=0}^x mathbb{P}(X = i) mean =sum {j=0}^infty… …
5Rasch model — Rasch models are used for analysing data from assessments to measure things such as abilities, attitudes, and personality traits. For example, they may be used to estimate a student s reading ability from answers to questions on a reading… …
6Generalized linear model — In statistics, the generalized linear model (GLM) is a flexible generalization of ordinary least squares regression. It relates the random distribution of the measured variable of the experiment (the distribution function ) to the systematic (non …
7Traffic generation model — A traffic generation model is a stochastic model of the traffic flows or data sources in a communication network, for example a cellular network or a computer network. A packet generation model is a traffic generation model of the packet flows or …
8Watts and Strogatz model — The Watts and Strogatz model is a random graph generation model that produces graphs with small world properties, including short average path lengths and high clustering. It was proposed by Duncan J. Watts and Steven Strogatz in their joint 1998 …
9Mixture model — See also: Mixture distribution In statistics, a mixture model is a probabilistic model for representing the presence of sub populations within an overall population, without requiring that an observed data set should identify the sub population… …
10Constellation model — The constellation model is a probabilistic, generative model for category level object recognition in computer vision. Like other part based models, the constellation model attempts to represent an object class by a set of N parts under mutual… …
