scholarly journals Completely solvable stochastic Hamiltonian system describing a continuous-time integrated climate-economy model

JSIAM Letters ◽  
2021 ◽  
Vol 13 (0) ◽  
pp. 5-8
Author(s):  
Jirô Akahori ◽  
Kensuke Nagata ◽  
Kota Suzuki
Keyword(s):  
Hamiltonian System ◽  
Continuous Time ◽  
Economy Model

Discrete-Time Equivalent of Continuous-Time Filtering Processes

1981 ◽  
Vol 103 (4) ◽  
pp. 417-419 ◽  
Author(s):  
Bernard Friedland
Keyword(s):  
Hamiltonian System ◽  
Discrete Time ◽  
Kalman Filtering ◽  
Continuous Time ◽  
Finite Time ◽  
Transition Matrix ◽  
Time Interval ◽  
Finite Time Interval ◽  
Filtering Problem

The continuous-time Kalman filtering problem over a finite time interval can be made equivalent to a discrete-time filtering problem. The matrices in the latter are related to the submatrices of the transition matrix of a Hamiltonian system that corresponds to the continuous-time filtering problem.

Heavy Tails of Discounted Aggregate Claims in the Continuous-Time Renewal Model

2007 ◽  
Vol 44 (02) ◽  
pp. 285-294 ◽  
Author(s):  
Qihe Tang
Keyword(s):  
Asymptotic Formula ◽  
Continuous Time ◽  
Heavy Tails ◽  
Tail Behavior ◽  
Renewal Model ◽  
Discounted Aggregate Claims ◽  
Aggregate Claims ◽  
Tail Asymptotic

We study the tail behavior of discounted aggregate claims in a continuous-time renewal model. For the case of Pareto-type claims, we establish a tail asymptotic formula, which holds uniformly in time.

Hierarchical Bayesian continuous time dynamic modeling.

2018 ◽  
Vol 23 (4) ◽  
pp. 774-799 ◽  
Author(s):  
Charles C. Driver ◽  
Manuel C. Voelkle
Keyword(s):  
Dynamic Modeling ◽  
Continuous Time ◽  
Hierarchical Bayesian ◽  
Time Dynamic

Continuous Time Controller Design

IEE Review ◽  
1991 ◽  
Vol 37 (6) ◽  
pp. 228
Author(s):  
Stephen Barnett
Keyword(s):  
Continuous Time ◽  
Controller Design

MANAGEMENT OF THE SUCCESS OF STUDENT’S LEARNING BASED ON THE MARKOV MODEL

2018 ◽  
pp. 4-11
Author(s):  
M. V. Noskov ◽  
M. V. Somova ◽  
I. M. Fedotova
Keyword(s):  
Information System ◽  
Markov Process ◽  
Continuous Time ◽  
Information Technologies ◽  
Educational Process ◽  
Automated Information System ◽  
The Subject ◽  
The University ◽  
Independent Work ◽  
Near Future

The article proposes a model for forecasting the success of student’s learning. The model is a Markov process with continuous time, such as the process of “death and reproduction”. As the parameters of the process, the intensities of the processes of obtaining and assimilating information are offered, and the intensity of the process of assimilating information takes into account the attitude of the student to the subject being studied. As a result of applying the model, it is possible for each student to determine the probability of a given formation of ownership of the material being studied in the near future. Thus, in the presence of an automated information system of the university, the implementation of the model is an element of the decision support system by all participants in the educational process. The examples given in the article are the results of an experiment conducted at the Institute of Space and Information Technologies of Siberian Federal University under conditions of blended learning, that is, under conditions when classroom work is accompanied by independent work with electronic resources.

A Political Economy Model of a Research University

2009 ◽  
pp. 132-143
Author(s):  
K. Sonin ◽  
I. Khovanskaya
Keyword(s):  
Organizational Structure ◽  
Information Structure ◽  
Research University ◽  
Hiring Decisions ◽  
Voting Rules ◽  
Economy Model ◽  
Trade Offs ◽  
Political Economic ◽  
Optimal Incentives

Hiring decisions are typically made by committees members of which have different capacity to estimate the quality of candidates. Organizational structure and voting rules in the committees determine the incentives and strategies of applicants; thus, construction of a modern university requires a political structure that provides committee members and applicants with optimal incentives. The existing political-economic model of informative voting typically lacks any degree of variance in the organizational structure, while political-economic models of organization typically assume a parsimonious information structure. In this paper, we propose a simple framework to analyze trade-offs in optimal subdivision of universities into departments and subdepartments, and allocation of political power.

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