AnaSimFPT(Sim.DiffProc)
AnaSimFPT()所属R语言包:Sim.DiffProc
Simulation The First Passage Time FPT For A Simulated Diffusion Process
为模拟扩散过程模拟的首出时FPT
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Simulation M-samples of the first passage time (FPT) by a simulated diffusion process with a fixed the threshold v.
仿真的M-样品时间(FPT)的第一通道与一个固定的阈值由模拟扩散过程诉
用法----------Usage----------
AnaSimFPT(N, M, t0, Dt, T = 1, X0, v, drift, diff,
ELRENA=c("No","Yes","Mean","Median"),
Output = FALSE, Methods = c("Euler", "Milstein",
"MilsteinS","Ito-Taylor", "Heun", "RK3"), ...)
----------Arguments----------
参数:N
size of the diffusion process.
的扩散过程的大小。
参数:M
size of the FPT.
的FPT大小。
参数:t0
initial time.
初始时间。
参数:Dt
time step of the simulation (discretization).
时间步长的仿真(discretization)。
参数:T
final time.
最后的时间。
参数:X0
initial value of the process at time t0.
初始值的过程中,在时间t0。
参数:v
threshold (Risk).
阈值(风险)。
参数:drift
drift coefficient: an expression of two variables t and x.
漂移:表达两个变量t和x。
参数:diff
diffusion coefficient: an expression of two variables t and x.
扩散系数:表达两个变量t和x。
参数:ELRENA
if ELRENA = "No" not eliminate NA (Not Available),and if ELRENA="Yes" eliminate NA (Not Available), or replace NA by : mean(FPT) ,median(FPT).
如果ELRENA = "No"不能消除NA(不可用),如果ELRENA="Yes"消除NA(不可用),或更换不适用的:mean(FPT),<X >。
参数:Output
if Output = TRUE write a Output to an Excel (.csv).
如果Output = TRUE写的Output到Excel(CSV)。
参数:Methods
method of simulation ,see details snssde.
模拟的方法,详情请参阅snssde。
参数:...
Details
详细信息----------Details----------
The stochastic differential equation of is :
随机微分方程的是:
with a(t,X(t)) :drift coefficient and b(t,X(t)) :diffusion coefficient, W(t) is Wiener process.
a(t,X(t)) :drift coefficient和b(t,X(t)) :diffusion coefficient,W(t)是维纳过程。
We take interest in the random variable tau "first passage time", is defined by :
我们有兴趣在随机变量tau“首次穿越时间”,被定义为:
with v is the threshold.
v is the threshold。
For more detail consulted References.
对于更详细的咨询References。
值----------Value----------
Random variable tau "FPT".
随机变量头“FPT”。
注意----------Note----------
Time of Calculating
计算时间
The Ornstein-Uhlenbeck Process (example) drift <- expression(-5*x) diff <- expression(1)
Ornstein-Uhlenbeck过程(例如)漂移< - 表达(-5 * x)的差异 - 式(1)
system.time(AnaSimFPT(N=1000, M=30, t0=0, Dt=0.001, T = 1, X0=10, v=0.05,drift, diff, ELRENA ="No", Output = FALSE))
system.time(AnaSimFPT(N = 1000,M = 30,T0 = 0,,DT = 0.001,T = 1,X0 = 10,V = 0.05,漂移,差异,ELRENA =“否”,输出= FALSE))
utilisateur systeme ecoule
utilisateur SYSTEME ecoule
1.89 0.55 2.62
1.89 0.55 2.62
system.time(AnaSimFPT(N=1000, M=100, t0=0, Dt=0.001, T = 1, X0=10, v=0.05,drift, diff, ELRENA ="No", Output = FALSE))
system.time(AnaSimFPT(N = 1000,M = 100,T0 = 0,,DT = 0.001,T = 1,X0 = 10,V = 0.05,漂移,差异,ELRENA =“否”,输出= FALSE))
utilisateur systeme ecoule
utilisateur SYSTEME ecoule
5.74 1.64 7.78
5.74 1.64 7.78
system.time(AnaSimFPT(N=1000, M=500, t0=0, Dt=0.001, T = 1, X0=10, v=0.05,drift, diff, ELRENA ="Mean", Output = FALSE))
system.time(AnaSimFPT(N = 1000,M = 500,T0 = 0,,DT = 0.001,T = 1,X0 = 10,V = 0.05,漂移,差异,ELRENA =“中庸”,输出= FALSE))
utilisateur systeme ecoule
utilisateur SYSTEME ecoule
26.07 7.78 37.93
26.07 7.78 37.93
system.time(AnaSimFPT(N=1000, M=500, t0=0, Dt=0.001, T = 1, X0=10, v=0.05,drift, diff, ELRENA ="Mean", Output = FALSE,Methods="RK3"))
system.time(AnaSimFPT(N = 1000,M = 500,T0 = 0,DT = 0.001,T = 1,X0 = 10,V = 0.05,漂移,差异,ELRENA =“中庸”,输出= FALSE,方法=“RK3”))
utilisateur systeme ecoule
utilisateur SYSTEME ecoule
125.64 8.90 150.85
125.64 8.90 150.85
(作者)----------Author(s)----------
Boukhetala Kamal, Guidoum Arsalane.
参考文献----------References----------
K.Boukhetala, Kernel density of the exit time in a simulated diffusion, les Annales Maghrebines De L ingenieur, Vol , 12, N Hors Serie. Novembre 1998, Tome II, pp 587-589.
参见----------See Also----------
AnaSimX Simulation M-Samples of Random Variable X(v[t]) For A Simulated Diffusion Process, tho_M1 Simulation The FPT For Attractive Model(S = 1,Sigma), tho_M1 Simulation The FPT For Attractive Model(S >= 2,Sigma), tho_02diff Simulation FPT For Attractive Model for 2-Diffusion Processes.
AnaSimX样品随机变量的仿真M-所述(V [T])扩散过程的模拟,tho_M1模拟FPT有吸引力的模型(S = 1,Sigma公司),tho_M1模拟FPT有吸引力的模型(S> = 2,Sigma公司),tho_02diff有吸引力的型号为2 - 扩散过程的模拟FPT。
实例----------Examples----------
## Example 1[#示例1]
## tau = inf(t>=0 \ X(t) <= v [#头= INF(T> = 0 \ X(T)<= V]
## Ornstein-Uhlenbeck Process or Gaussian Diffusion Models[#Ornstein-Uhlenbeck过程或高斯扩散模型]
v = 0.05
drift <- expression(5*(-2-x))
diff <- expression(1)
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.001, T = 1, X0=10, v=0.05, drift,
diff,ELRENA ="No", Output = FALSE)
summary(tau)
hist(tau)
plot(density(tau,kernel ="gaussian"),col="red")
v = -0.05
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.001, T = 1, X0=10, v=-0.05, drift,
diff,ELRENA ="No", Output = FALSE)
summary(tau)
hist(tau)
plot(density(tau,kernel ="gaussian"),col="red")
## Attention[#注意]
v = -3
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.001, T = 1, X0=10, v=-3, drift,
diff,ELRENA ="No", Output = FALSE)
## Example 2[#示例2]
## tau = inf(t>=0 \ X(t) >= v )[#头= INF(T> = 0 \ X(T)> = V)]
v = 1
drift <- expression(2*(3-x))
diff <- expression(0.1)
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.001, T = 1, X0=-5, v=1, drift,
diff,ELRENA ="No", Output = FALSE)
summary(tau)
hist(tau)
plot(density(tau,kernel ="gaussian"),col="red")
v = 3
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.01, T = 1, X0=-5, v=3, drift,
diff,ELRENA ="No", Output = FALSE)
summary(tau)
hist(tau)
plot(density(tau,kernel ="gaussian"),col="red")
v = 3.1
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.01, T = 1, X0=-5, v=3.1, drift,
diff,ELRENA ="No", Output = FALSE)
## Remplaced NA by mean(tau) or median(tau)[#Remplaced NA(头)或中位数(头)]
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.01, T = 1, X0=-5, v=3.1, drift,
diff,ELRENA ="Yes", Output = FALSE)
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.01, T = 1, X0=-5, v=3.1, drift,
diff,ELRENA ="Mean", Output = FALSE)
AnaSimFPT(N=1000, M=30, t0=0, Dt=0.01, T = 1, X0=-5, v=3.1, drift,
diff,ELRENA ="Median", Output = FALSE)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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