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応用および計算数学ジャーナル

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音量 10, 問題 2 (2021)

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Behavior of a State-dependent Functional Differential Equation

Yin-Wei Lin, Tzon-Tzer Lu

This paper deals with the state-dependent functional differential equations x(x(t)). We give the strict proof of qualitative properties that Eder’s case and the solution of the state-dependent differential equation is not unique. In some conditions, we also extend Eder’s case.

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Coefficient Inequalities for Uniformly P-Valent Starlike and Convex Functions

Vandna Agnihotria 1, Ran Singh 2

In this paper we obtain some coefficient inequalities for subclasses of uniformly p−valent starlike and convex functions in the open unit disk denoted by SDp (β, α) and KDp (β, α). Growth bounds and distortion bounds are discussed for functions in these classes. For different values of the parameters p, α and β our results of this paper generalize those obtained by several authors in the literature.

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US Capital Gains Tax Rate Using Markov Chains

Brian Trowbridge

Using Markov-chains (formally a Markov process or Markov system) we will show how to estimate the probabilities of a capital gains tax rate changing from its current rate to another rate within a certain number of years. It is important to recognize that capital gains rates in the United States have their origins in every elected administration of the government that had the power to influence tax policy. The outcome of government elections is dependent on chance factors such as periods of war and peace, economic recession and expansion, current fiscal and monetary policy, changes in population demographics, just to name a few. The delicate balance between the government and the dynamic society that shapes tax policy is difficult to predict using deterministic modeling. Therefore, we look to stochastic modeling using the Markov-Chain processes to see if it could be of use in creating a useful model for capital gains tax rates in the United States

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Complexity in Mathematics

Artur Sowa

              

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