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[PDF] Top 20 Modeling Election Problem by a Stochastic Differential Equation

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Modeling Election Problem by a Stochastic Differential Equation

Modeling Election Problem by a Stochastic Differential Equation

... The rate of support for a candidate depends on a number of factors, such as candidate’s party, election standpoint, personal prestige, world political situation and even order of applicants. Small factors, ... See full document

7

On Differential Growth Equation to Stochastic Growth Model Using Hyperbolic Sine Function in Height/Diameter Modeling of Pines

On Differential Growth Equation to Stochastic Growth Model Using Hyperbolic Sine Function in Height/Diameter Modeling of Pines

... growth equation (Zeide growth prediction method is very useful modeling growth and yield of trees due to lack of approximations in measuring the diameter of ... See full document

6

Portfolio Optimization Problem with Delay under Cox Ingersoll Ross Model

Portfolio Optimization Problem with Delay under Cox Ingersoll Ross Model

... optimization problem with ...Cox-Ingersoll-Ross stochastic volatility ...by stochastic delay differential ...Hamilton-Jacobin-Bellman equation and verification theorem, and the closed- ... See full document

19

Backward-forward linear-quadratic mean-field games with major and minor agents

Backward-forward linear-quadratic mean-field games with major and minor agents

... LQ problem by minimizing the initial ...ward stochastic differential equation (BSDE) while the minor agents are modeled by some (forward) stochastic differential equations ... See full document

27

A stochastic differential equation analysis of cerebrospinal fluid dynamics

A stochastic differential equation analysis of cerebrospinal fluid dynamics

... of modeling noise in CSF dynamics Broadly construed, noise arises from variations in fac- tors that influence the observed outcome – which is the ICP in this paper – but that have been omitted from the ... See full document

10

Dynkin game under g-expectation in continuous time

Dynkin game under g-expectation in continuous time

... of problem. Since this stopping game problem is an extension of the optimal stopping problem, the martingale approach has been used to find a pair of saddle point, and then the value function is ... See full document

13

On stochastic differential equations and a generalised Burgers equation

On stochastic differential equations and a generalised Burgers equation

... One can then discuss comprehensively the existence and uniqueness as well as the structure of solutions to the initial value problem for equation (1.1) by appealing the above argument with suitable choice ... See full document

14

Uncertainty propagation and quantification in a continuous time dynamical system

Uncertainty propagation and quantification in a continuous time dynamical system

... Itˆo stochastic differential equations (introduced by Japanese mathematician ...in modeling the stock price, the only information one has is about the past ...Itˆo stochastic ... See full document

45

A Stochastic Differential Equation Inventory Model

A Stochastic Differential Equation Inventory Model

... It has been recognized for some time that the demand for some items may be proportional to the inventory on display. Baker and Urban [1] argued that the demand rate of an item is of a polynomial functional form, ... See full document

17

A stochastic differential equation model for pest management

A stochastic differential equation model for pest management

... Especially, spraying of pesticides to crops is intended to reduce the population of pest, but can under some circumstances exacerbate a pest problem. This phenomenon, fre- quently called insecticide-induced ... See full document

13

Nonparametric Model Calibration for Derivatives

Nonparametric Model Calibration for Derivatives

... Their numerical resolution, based upon an alternating direction implicit scheme, produces a satisfactory fit under certain assumptions (confirmed by the theoretical difficulties met when studying them). When those ... See full document

26

A Stochastic Version of the Jansen and Rit Neural Mass Model: Analysis and Numerics

A Stochastic Version of the Jansen and Rit Neural Mass Model: Analysis and Numerics

... ordinary differential equations (ODEs), ...a stochastic process inheriting the analytical properties of the input process and requiring some framework of stochas- tic analysis for its mathematical ...a ... See full document

35

Stochastic differential equation for two-phase growth model

Stochastic differential equation for two-phase growth model

... Thus a modification to Zheng’s two-phase growth might be developed with respect to birth and processes. Unfortunately, some types of birth and death process are difficult to get their probability distribution, thus ... See full document

31

Sparse Grid Interpolation of Itˆo Stochastic Models in Epidemiology and Systems Biology

Sparse Grid Interpolation of Itˆo Stochastic Models in Epidemiology and Systems Biology

... Abstract—Computational modeling enhances our under- standing of seemingly incomprehensible biological ...Surrogate modeling using sparse grid interpolation can alleviate the burden associated with ... See full document

8

Application of the Kalman-Bucy filter in the stochastic differential equation for the modeling of RL circuit

Application of the Kalman-Bucy filter in the stochastic differential equation for the modeling of RL circuit

... the stochastic calculus to the problem of modeling electrical ...filtering problem have an important role in the theory of stochastic differential ...a stochastic model by ... See full document

7

A Mean Field Stochastic Maximum Principle for Optimal Control of Forward Backward Stochastic Differential Equations with Jumps via Malliavin Calculus

A Mean Field Stochastic Maximum Principle for Optimal Control of Forward Backward Stochastic Differential Equations with Jumps via Malliavin Calculus

... type stochastic control problem where the dynamics is governed by a forward and backward stochastic differential equa- tion (SDE) driven by Lévy processes and the information available to the ... See full document

17

Controllability of a Stochastic Neutral Functional Differential Equation Driven by a fBm

Controllability of a Stochastic Neutral Functional Differential Equation Driven by a fBm

... fractional differential equations and their applications are prominent, especially in modeling several complex phenomena such as anomalous diffusion of particles (see, for examples, [6] ...neutral ... See full document

15

Stochastic control representations for penalized backward stochastic differential equations

Stochastic control representations for penalized backward stochastic differential equations

... backward stochastic differential equation (penalized BSDE for short) to solve reflected backward stochastic differential equation (reflected BSDE for short), and they showed that ... See full document

25

Limit theorems for solutions of stochastic differential equation problems

Limit theorems for solutions of stochastic differential equation problems

... Limit Theorem, Stochastic Eigenvalue Problem, Stochastic Boundary Value Poblem, Differential Equation... At the research of physical and engineering problems it is of great.[r] ... See full document

37

Understanding the stochastic partial differential equation approach to smoothing

Understanding the stochastic partial differential equation approach to smoothing

... Correlation and smoothness are terms used to describe a wide variety of random quantities. In time, space, and many other domains, they both imply the same idea: quantities that occur closer together are more similar ... See full document

16

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