A Derivation of the Polytomous Rasch Model Based on the Most Probable Distribution Method

2014 ◽  
Vol 17 ◽  
Author(s):  
Stefano Noventa ◽  
Luca Stefanutti ◽  
Giulio Vidotto
Keyword(s):  
Rasch Model ◽  
Statistical Physics ◽  
Distribution Method ◽  
Principle Of Maximum Entropy ◽  
Probable Distribution ◽  
Item Characteristics ◽  
Latent Traits ◽  
Principle Of Maximum ◽  
Most Probable Distribution ◽  
Polytomous Rasch Model

AbstractBoltzmann’s most probable distribution method is applied to derive the Polytomous Rasch model as the distribution accounting for the maximum number of possible outcomes in a test while introducing latent traits, item characteristics, and thresholds as constraints to the system. Affinities and similarities of the present result with other derivations of the model are discussed in light of the conceptual frameworks of statistical physics and of the principle of maximum entropy.

Information mechanics

2017 ◽  
Author(s):  
Sandip Tiwari
Keyword(s):  
Information Flow ◽  
Irreversible Processes ◽  
State Machines ◽  
Science And Engineering ◽  
Von Neumann ◽  
Principle Of Maximum Entropy ◽  
Information Manipulation ◽  
Classical Quantum ◽  
Physical Laws ◽  
Principle Of Maximum

Information is physical, so its manipulation through devices is subject to its own mechanics: the science and engineering of behavioral description, which is intermingled with classical, quantum and statistical mechanics principles. This chapter is a unification of these principles and physical laws with their implications for nanoscale. Ideas of state machines, Church-Turing thesis and its embodiment in various state machines, probabilities, Bayesian principles and entropy in its various forms (Shannon, Boltzmann, von Neumann, algorithmic) with an eye on the principle of maximum entropy as an information manipulation tool. Notions of conservation and non-conservation are applied to example circuit forms folding in adiabatic, isothermal, reversible and irreversible processes. This brings out implications of fluctuation and transitions, the interplay of errors and stability and the energy cost of determinism. It concludes discussing networks as tools to understand information flow and decision making and with an introduction to entanglement in quantum computing.

scholarly journals To Be or to Have Been Lucky, That Is the Question

Philosophies ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 57
Author(s):  
Antony Lesage ◽  
Jean-Marc Victor
Keyword(s):  
High Risk ◽  
Maximum Entropy ◽  
Chronic Diseases ◽  
Statistical Test ◽  
Low Risk ◽  
Principle Of Maximum Entropy ◽  
Ex Ante ◽  
Social Opportunities ◽  
Global Population ◽  
Principle Of Maximum

Is it possible to measure the dispersion of ex ante chances (i.e., chances “before the event”) among people, be it gambling, health, or social opportunities? We explore this question and provide some tools, including a statistical test, to evidence the actual dispersion of ex ante chances in various areas, with a focus on chronic diseases. Using the principle of maximum entropy, we derive the distribution of the risk of becoming ill in the global population as well as in the population of affected people. We find that affected people are either at very low risk, like the overwhelming majority of the population, but still were unlucky to become ill, or are at extremely high risk and were bound to become ill.

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