The point distribution model is a model for representing the mean geometry of a shape and some statistical modes of geometric variation inferred from a training set of shapes.
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Taylor in 1995. The shapes are constrained by the PDM (pointdistributionmodel) Statistical Shape Model to vary only in ways seen in a training set of labelled...
exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process,...
respectively, and control the shape of the distribution. The beta distribution has been applied to model the behavior of random variables limited to...
observation belongs. Formally a mixture model corresponds to the mixture distribution that represents the probability distribution of observations in the overall...
probability distributions used in statistical modeling include the Poisson distribution, the Bernoulli distribution, the binomial distribution, the geometric...
theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable...
the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters...
probability theory and statistics, the Weibull distribution /ˈwaɪbʊl/ is a continuous probability distribution. It models a broad range of random variables, largely...
consumers such as with 3D printing Distribution of elements in the distributed-element model of electric circuits Trip distribution, part of the four-step transportation...
distribution (although in practice, noise is rarely added during the decoding stage). By mapping a point to a distribution instead of a single point,...
Poisson distribution is a useful model is the number of radioactive decay events during a fixed observation period.[citation needed] The distribution was...
represents a discrete version of this approach, taking advantage of the pointdistributionmodel to restrict the shape range to an explicit domain learnt from a...
following Jebara (2004): A generative model is a statistical model of the joint probability distribution P ( X , Y ) {\displaystyle P(X,Y)} on a given observable...
the two-pointdistributions including the Bernoulli distribution have a lower excess kurtosis, namely −2, than any other probability distribution. The Bernoulli...
parameterization is common for modeling waiting times, such as the time until death, where it often takes the form of an Erlang distribution for integer k values...
theory and statistics, the negative binomial distribution is a discrete probability distribution that models the number of failures in a sequence of independent...
one might model the distribution of all naturally-occurring photos. Each image is a point in the space of all images, and the distribution of naturally-occurring...
where the Poisson point process is used. The two properties are not logically independent; indeed, the Poisson distribution of point counts implies the...
exponential family of distributions is a generalization of an exponential family and the exponential dispersion model of distributions and includes those...
The discrete uniform distribution, where all elements of a finite set are equally likely. This is the theoretical distributionmodel for a balanced coin...
{P}}} contains the true distribution, and in practice that is rarely the case. Indeed, as Burnham & Anderson state, "A model is a simplification or approximation...
modelling the delta "function" rigorously involves the use of limits or, as is common in mathematics, measure theory and the theory of distributions....
Tweedie distributions are a special case of exponential dispersion models and are often used as distributions for generalized linear models. The Tweedie...
probability theory, the multinomial distribution is a generalization of the binomial distribution. For example, it models the probability of counts for each...
beta distribution, hence its alternative name of multivariate beta distribution (MBD). Dirichlet distributions are commonly used as prior distributions in...
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