scholarly journals Determining statistical dominance by linear programming

1988 ◽  
Vol 29 (3) ◽  
pp. 266-269
Author(s):  
Ross G. Drynan
Keyword(s):  
Linear Programming ◽  
Partial Information ◽  
Sufficient Conditions ◽  
Vector Dominance ◽  
Discrete States ◽  
Linear Partial Information ◽  
States Of Nature ◽  
Necessary And Sufficient ◽  
One Act ◽  
General Vector

AbstractThis note generalises the necessary and sufficient conditions for one act to be dominated by another when the two acts available to the decision maker have outcomes contingent on discrete states of nature whose probabilities of occurrence are known only to the extent of linear partial information. The generalisation relates to the dominance of an act by a set of acts. The presentation is in terms of general vector dominance, of which statistical dominance is only a particular case.

scholarly journals Consensus Analysis for High-Order Multi-Agent Systems without or with Delays

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Zhengxin Wang ◽  
Yang Cao
Keyword(s):  
Partial Information ◽  
Sufficient Conditions ◽  
High Order ◽  
Consensus Problem ◽  
Multi Agent Systems ◽  
Consensus Protocol ◽  
Consensus Analysis ◽  
Agent Systems ◽  
Multi Agent ◽  
Necessary And Sufficient

This paper studies the consensus problem for a high-order multi-agent systems without or with delays. Consensus protocols, which only depend on the own partial information of agents and partial relative information with its neighbors, are proposed for consensus and quasi-consensus, respectively. Firstly, some lemmas are presented, and then a necessary and sufficient condition for guaranteeing the consensus is established under the consensus protocol without delays. Furthermore, communication delays are considered. Some necessary and sufficient conditions for solving quasi-consensus problem with delays are obtained. Finally, some simulations are given to verify the theoretical results.

scholarly journals INFORMATION AND OPTIMAL INVESTMENT IN DEFAULTABLE ASSETS

2014 ◽  
Vol 17 (08) ◽  
pp. 1450050 ◽  
Author(s):  
GIULIA DI NUNNO ◽  
STEFFEN SJURSEN
Keyword(s):  
Counting Process ◽  
Partial Information ◽  
A Priori ◽  
Sufficient Conditions ◽  
Random Measure ◽  
Optimal Investment ◽  
Terminal Time ◽  
Necessary And Sufficient ◽  
Forward Integration ◽  
Different Levels

We study optimal investment in an asset subject to risk of default for investors that rely on different levels of information. The price dynamics can include noises both from a Wiener process and a Poisson random measure with infinite activity. The default events are modeled via a counting process in line with large part of the literature in credit risk. In order to deal with both cases of inside and partial information we consider the framework of the anticipating calculus of forward integration. This does not require a priori assumptions typical of the framework of enlargement of filtrations. We find necessary and sufficient conditions for the existence of a locally maximizing portfolio of the expected utility at terminal time. We consider a large class of utility functions. In addition we show that the existence of the solution implies the semi-martingale property of the noises driving the stock. Some discussion on unicity of the maxima is included.

scholarly journals An inverse problem for the integro-differential Dirac system with partial information given on the convolution kernel

2019 ◽  
Vol 27 (2) ◽  
pp. 151-157 ◽  
Author(s):  
Natalia Pavlovna Bondarenko
Keyword(s):  
Inverse Problem ◽  
Uniqueness Theorem ◽  
Partial Information ◽  
A Priori ◽  
Sufficient Conditions ◽  
Convolution Kernel ◽  
Dirac System ◽  
Integral Term ◽  
Necessary And Sufficient ◽  
The Uniqueness Theorem

AbstractAn integro-differential Dirac system with an integral term in the form of convolution is considered. We suppose that the convolution kernel is known a priori on a part of the interval, and recover it on the remaining part, using a part of the spectrum. We prove the uniqueness theorem, provide an algorithm for the solution of the inverse problem together with necessary and sufficient conditions for its solvability.

scholarly journals Structural Controllability of Boolean Control Networks under Partial Information

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qinyao Pan ◽  
Jie Zhong ◽  
Shalin Tong ◽  
Bowen Li ◽  
Xiaoxu Liu
Keyword(s):  
Boolean Functions ◽  
Partial Information ◽  
Sufficient Conditions ◽  
Vital Role ◽  
Boolean Networks ◽  
Lactose Operon ◽  
Control Networks ◽  
Structural Controllability ◽  
Necessary And Sufficient ◽  
Theoretical Results

It is worth noting that both nodes’ coupling connections and logical updating functions play a vital role in state evolutions of Boolean networks (BNs). In this paper, a new concept named structural controllability (SC) about Boolean control networks (BCNs) with known partial information on nodes’ connections is studied. Then, by referring to semi-tensor product (STP) techniques, several types of SC are presented according to different issues of Boolean functions. Thereafter, several necessary and sufficient conditions are derived for SC of BCNs. Finally, a biological model of the lactose operon in Escherichia coli is simulated to show the effectiveness of the main theoretical results.

scholarly journals Using Enhanced Russell Model to Solve Inverse Data Envelopment Analysis Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
G. R. Jahanshahloo ◽  
F. Hosseinzadeh Lotfi ◽  
M. Rostamy-Malkhalifeh ◽  
S. Ghobadi
Keyword(s):  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Sufficient Conditions ◽  
Necessary And Sufficient Conditions ◽  
Multiple Objective ◽  
Multiple Objective Linear Programming ◽  
Data Envelopment ◽  
Input Output ◽  
Pareto Solutions ◽  
Necessary And Sufficient

This paper studies the inverse data envelopment analysis using the nonradial enhanced Russell model. Necessary and sufficient conditions for inputs/outputs determination are introduced based on Pareto solutions of multiple-objective linear programming. In addition, an approach is investigated to identify extra input/lack output in each of input/output components (maximum/minimum reduction/increase amounts in each a of input/output components). In addition, the following question is addressed: if among a group of DMUs, it is required to increase inputs and outputs to a particular unit and assume that the DMU maintains its current efficiency level with respect to other DMUs, how much should the inputs and outputs of the DMU increase? This question is discussed as inverse data envelopment analysis problems, and a technique is suggested to answer this question. Necessary and sufficient conditions are established by employing Pareto solutions of multiple-objective linear programming as well.

scholarly journals Positivel1State-Bounding Observer Design for Positive Interval Markovian Jump Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Di Zhang ◽  
Qingling Zhang ◽  
Borong Lyu
Keyword(s):  
Linear Programming ◽  
Sufficient Conditions ◽  
Observer Design ◽  
Markovian Jump Systems ◽  
Programming Approach ◽  
Markovian Jump ◽  
Parameter Uncertainties ◽  
Positive Markovian Jump Systems ◽  
Necessary And Sufficient ◽  
Jump Systems

This paper studies the problem of positivel1state-bounding observer design for a class of positive Markovian jump systems with interval parameter uncertainties by a linear programming approach. For the first, necessary and sufficient conditions are obtained for stochastic stability andl1performance of positive Markovian jump systems by an “equivalent” deterministic positive linear system. Furthermore, based on the results obtained in this paper, sufficient conditions for the existence of the positivel1state-bounding observer are derived. The conditions can be solved in terms of linear programming. Finally, a numerical example is used to illustrate the effectiveness of the results obtained.

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