On strong markov property of 運(yùn)動(dòng)的強(qiáng)馬氏性及應(yīng)用
On markov property of the risk reserve processes and continuous - time risk models with discete - type inter - arrival times 盈余過(guò)程的馬氏性與索賠到達(dá)間隔分布為離散型的連續(xù)時(shí)間風(fēng)險(xiǎn)模型
Third we suppose that the effect of the break - down is delayed . usually , we can say that the process is markov process if the durations of working and repair have negative - exponentials , so we take the markov process as the original system , the system set up by modeling as the new system . new systems have not the markov properties , which is worth to study 因?yàn)橥ǔ<僭O(shè)部件的工作與維修時(shí)間的隨機(jī)變量是服從指數(shù)分布的,因此可以用馬爾可夫過(guò)程來(lái)描述系統(tǒng),但是,在建立模型之后的系統(tǒng),稱為新系統(tǒng),不具有馬爾可夫性,因此這個(gè)新系統(tǒng)的可靠性指標(biāo)的給出就成為一個(gè)值得研究的問(wèn)題。
The introduction black - scholes models still assumed , namely the introduction of modern process ( wiener process , also called brownian motion ) to save the stock yield random fluctuations , weak markets and the effectiveness of the use of consistent share of the techniques ( ( markov property ) to describe the stock price change random process , the use of risk - neutral pricing theory through the analysis of the nature of asset price process martingale , established european style to the value of stock options with mathematical models 本文仍然引入black - scholes的模型假定,也即引入維納過(guò)程( wienerprocess , alsocalledbrownianmotion )來(lái)刻畫股票收益率的隨機(jī)波動(dòng),采用與弱型市場(chǎng)有效性相一致的股價(jià)的馬爾可夫性( markovproperty )來(lái)描述股票價(jià)格變化的隨機(jī)過(guò)程,運(yùn)用風(fēng)險(xiǎn)中性定價(jià)理論,通過(guò)分析資產(chǎn)價(jià)格過(guò)程鞅的性質(zhì),建立了歐式再裝股票期權(quán)價(jià)值的數(shù)學(xué)模型。
For quantitative analysis of the combat platform fire application , the markov chain model of combat platform with reciprocal striking , hasty break through and shooting to dense target is studied by setting up markov chain which state and time are discrete according to the markov property in this process 摘要針對(duì)定量分析戰(zhàn)斗平臺(tái)火力運(yùn)用問(wèn)題,根據(jù)該過(guò)程所具有的馬爾可夫性特點(diǎn),將其描述為狀態(tài)離散、時(shí)間離散的馬爾可夫鏈,由此研究了一對(duì)一格斗、倉(cāng)促突破戰(zhàn)斗、對(duì)密集目標(biāo)群射擊等情況下的馬爾可夫鏈模型。
In probability theory and statistics, the term Markov property refers to the memoryless property of a stochastic process. It is named after the Russian mathematician Andrey Markov.