# JPD

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AcronymDefinition
JPDJacksonville Police Department (North Carolina)
JPDJuvenile Probation Department
JPDJackson Police Department
JPDJoint Probability Density
JPDJournal of Pedagogic Development (University of Bedforshire; UK)
JPDJoint Probability Distribution
JPDJoliet Police Department (Illinois, USA)
JPDJoint Planning Document
JPDJoint PhotoDefiner (lossy comression)
JPDJapan Process Development (est. 1967)
JPDJoint Potential Designator
JPDJava Process Definition (Service Oriented Architecture)
JPDJuvenile Periodontitis
JPDJust Plain Dumb
JPDJunior Professional Development (program)
JPDJoint Personnel Database
JPDJohnstown Police Department
JPDJohnston Police Department (Johnston, RI, USA)
JPDJobs per Day
References in periodicals archive ?
Based on the connections between the node and its father node expressed in the above definitions, a function of joint probability distribution that contains all of the nodes can be deduced.
A joint probability distribution is the probability distribution of a multidimensional vector--each dimension representing a separate variable within a study.
Mathematically, a BNs represents a joint probability distribution P over a set of random variables X = {[X.
BNs address the problems of storing and representing the joint probability distribution of a large number of random variables and doing Bayesian inference with these variables.
The joint probability distribution in G describes the given knowledge base, and Bayesian network expresses the knowledge model of a problem domain.
As discussed earlier, the simulations for the states are correlated: the joint probability distribution of the 51 election outcomes includes uncertainty about the national swing as well as state-by-state fluctuations.
The approach requires estimation of joint probability distributions from a four-dimensional joint feature histogram.
Table 3: Joint Probability Distribution for International Trips Selected Acceptance Rate\Actual Sales Low Base High Below Average 6.
For a given query, the system will arrive at a joint probability distribution over the elementary event space [Omega] = X x R, where X is a vector of document attributes, and R = {0, 1} corresponds to judgments of relevance.
It will be shown below that the signs and the firm's equilibrium under uncertainty depend on: (i) the relationship between the output and factor markets as determined by the properties of the joint probability distribution function of prices and (ii) the firm's attitude toward risk.
n])} uniquely determines a joint probability distribution for those variables.
And, if we had taken as our fundamental concept the joint probability distribution of causes and effects together, perfect symmetry between past and future would have been the upshot.
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