翻訳と辞書 Words near each other ・ Tau Serpentis ・ Tau Sigma ・ Tau Sigma Delta ・ Tau Sigma Phi ・ Tau Taa Wana ・ Tau tau ・ Tau Tauri ・ Tau Ursae Majoris ・ Tau Virginis ・ Tau Zero ・ Tau'ri characters in Stargate ・ Tau'uta Reds ・ Tau, American Samoa ・ Tau, Norway ・ Tau-gu ・ Tau-leaping ・ Tau-protein kinase ・ Tau-Titi ・ Tau1 Aquarii ・ Tau1 Arietis ・ Tau1 Capricorni ・ Tau1 Eridani ・ Tau1 Gruis ・ Tau1 Gruis b ・ Tau1 Lupi ・ Tau1 Serpentis ・ Tau2 Aquarii ・ Tau2 Arietis ・ Tau2 Capricorni ・ Tau2 Eridani Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Tau-leaping ： ウィキペディア英語版 Tau-leaping In probability theory, tau-leaping, or τ-leaping, is an approximate method for the simulation of a stochastic system. It is based on the Gillespie algorithm, performing all reactions for an interval of length tau before updating the propensity functions. By updating the rates less often this sometimes allows for more efficient simulation and thus the consideration of larger systems. Many variants of the basic algorithm have been considered. ==Algorithm== The algorithm is analogous to the Euler method for deterministic systems, but instead of making a fixed change $x(t+\backslash tau)=x(t)+\backslash tau\; x\text{'}(t)$ the change is $x(t+\backslash tau)=x(t)+P(\backslash tau\; x\text{'}(t))$ where $P(\backslash tau\; x\text{'}(t))$ is a Poisson distributed random variable with mean $\backslash tau\; x\text{'}(t)$. Given a state $\backslash mathbf(t)=\backslash$ with events $E\_j$ occurring at rate $R\_j(\backslash mathbf(t))$ and with state change vectors $\backslash mathbf\_j$ (where $i$ indexes the state variables, and $j$ indexes the events), the method is as follows: # Initialise the model with initial conditions $\backslash mathbf(t\_0)=\backslash$. # Calculate the event rates $R\_j(\backslash mathbf(t))$. # Choose a time step $\backslash tau$. This may be fixed, or by some algorithm dependent on the various event rates. # For each event $E\_j$ generate $K\_j\; \backslash sim\; \backslash text(R\_j\backslash tau)$, which is the number of times each event occurs during the time interval $[t,t+\backslash tau)$. # Update the state by #:$\backslash mathbf(t+\backslash tau)=\backslash mathbf(t)+\backslash sum\_j\; K\_jv\_$ #:where $v\_$ is the change on state variable $X\_i$ due to event $E\_j$. At this point it may be necessary to check that no populations have reached unrealistic values (such as a population becoming negative due to the unbounded nature of the Poisson variable $K\_j$). # Repeat from Step 2 until some desired condition is met (e.g. a particular state variable reaches 0, or time $t\_1$ is reached). 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Tau-leaping」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.