arfimadistribution-methods(rugarch)
arfimadistribution-methods()所属R语言包：rugarch
function: ARFIMA Parameter Distribution via Simulation
功能：通过模拟的的ARFIMA参数分布
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Method for simulating and estimating the parameter distribution from an ARFIMA models as well as the simulation based consistency of the estimators given the
方法模拟和估计参数分布的ARFIMA模型以及基于仿真的估计量的一致性
用法----------Usage----------
arfimadistribution(fitORspec, n.sim = 2000, n.start = 1, m.sim = 100,
recursive = FALSE, recursive.length = 6000, recursive.window = 1000,
prereturns = NA, preresiduals = NA, rseed = NA,
custom.dist = list(name = NA, distfit = NA, type = "z"), mexsimdata = NULL,
fit.control = list(), solver = "solnp", solver.control = list(),
parallel = FALSE, parallel.control = list(pkg = c("multicore", "snowfall"),
cores = 2), ...)
参数----------Arguments----------
参数：fitORspec
Either an ARFIMA fit object of class ARFIMAfit or alternatively an ARFIMA specification object of class ARFIMAspec with valid parameters supplied via the fixed.pars argument in the specification.
无论是一个的ARFIMA适合对象类ARFIMAfit或者一个的ARFIMA规范对象的类ARFIMAspec提供有效的参数通过fixed.pars参数的规范。
参数：n.sim
The simulation horizon.
模拟的视野。
参数：n.start
The burn-in sample.
老化的样品。
参数：m.sim
The number of simulations.
的模拟次数。
参数：recursive
Whether to perform a recursive simulation on an expanding window.
是否执行递归模拟于扩大窗口。
参数：recursive.length
If recursive is TRUE, this indicates the final length of the simulation horizon, with starting length n.sim.
如果recursive是TRUE时，表示最终长度的模拟地平线，的起始长度n.sim。
参数：recursive.window
If recursive is TRUE, this indicates the increment to the expanding window. Together with recursive.length, it determines the total number of separate and increasing length windows which will be simulated and fitted.
如果recursive是TRUE，这表明增量扩展。再加上recursive.length，它决定了总人数的独立和日益增加的落地窗将模拟和拟合。
参数：prereturns
Allows the starting return data to be provided by the user.
允许起始返回的数据要由用户提供的。
参数：preresiduals
Allows the starting residuals to be provided by the user.
允许起始要由用户提供的残差。
参数：rseed
Optional seeding value(s) for the random number generator.
可选的随机数生成器的种子值（S）。
参数：custom.dist
Optional density with fitted object from which to simulate.
可选密度，合身的对象来模拟。
参数：mexsimdata
Matrix of simulated external regressor-in-mean data. If the fit object contains external regressors in the mean equation, this must be provided.
矩阵外部模拟的回归量平均数据。如果适合的对象包含外部在均值方程的回归，这必须被提供。
参数：solver
One of either “nlminb” or “solnp”.
之一“nlminb”或“solnp”。
参数：solver.control
Control arguments list passed to optimizer.
控制参数列表传递给优化。
参数：fit.control
Control arguments passed to the fitting routine (as in the arfimafit method).
控制参数传递到配件常规（如在arfimafit方法）。
参数：parallel
Whether to make use of parallel processing on multicore systems.
是否利用多核系统上的并行处理。
参数：parallel.control
The parallel control options including the type of package for performing the parallel calculations ("multicore" for non-windows O/S and "snowfall" for all O/S), and the number of cores to make use of.
并行控制选项，包括包的类型进行并行计算（多核非Windows O / S和“降雪”，所有的O / S），核心数量的利用。
参数：...
.
。
Details
详细信息----------Details----------
This method facilitates the simulation and evaluation of the uncertainty of ARFIMA model parameters. The recursive option also allows the evaluation of the simulation based consistency (in terms of sqrt(N) ) of the parameters as the length (n.sim) of the data increases, in the sense of the root mean square error (rmse) of the difference between the simulated and true (hypothesized) parameters.<br> This is an expensive function, particularly if using the recursive option, both on memory and CPU resources, performing many re-fits of the simulated data in order to generate the parameter distribution.
这种方法有利于ARFIMA模型参数的不确定性的仿真和评估。递归选项还允许评估的基于仿真的一致性（方面的sqrt（N））的参数作为的长度（n.sim）的数据的增加，在这个意义上的根均方误差（RMSE）模拟的和真实的（假设）参数之间的差异。<br>此是一个昂贵的功能，尤其是当使用recursive选项，无论是在内存和CPU资源，执行许多重新适合的模拟数据，以便以生成参数分布。
值----------Value----------
A ARFIMAdistribution object containing details of the ARFIMA simulated parameters distribution.
AARFIMAdistribution对象，其中包含细节的ARFIMA模拟参数分布。
（作者）----------Author(s)----------
Alexios Ghalanos
实例----------Examples----------
## Not run: [＃不运行：]
spec = arfimaspec( mean.model = list(armaOrder = c(2,2), include.mean = TRUE,
arfima = FALSE), distribution.model = "norm", fixed.pars = list(ar1=0.6,
ar2=0.21, ma1=-0.7, ma2=0.3, mu = 0.02, sigma = 0.02))
dist = arfimadistribution(spec, n.sim = 2000, n.start = 100, m.sim = 100,
recursive = TRUE, recursive.length = 10000, recursive.window = 1000)
# slots:[插槽：]
slotNames(dist)
# methods:[方法：]
# summary[总结]
show(dist)
# as.data.frame(...., window, which=c("rmse", "stats", "coef", "coefse"))[as.data.frame（......，窗口，= C（RMSE“，”统计“，”系数“，”coefse“），）]
# default[默认]
as.data.frame(dist)
as.data.frame(dist, window = 1, which = "rmse")
as.data.frame(dist, window = 1, which = "stats")
as.data.frame(dist, window = 1, which = "coef")
as.data.frame(dist, window = 1, which = "coefse")
as.data.frame(dist, window = 8, which = "rmse")
as.data.frame(dist, window = 8, which = "stats")
as.data.frame(dist, window = 8, which = "coef")
as.data.frame(dist, window = 8, which = "coefse")
# create some plots[创建一些图]
# []
nwindows = dist@dist$details$nwindows
# 2000/3000/4000/5000/6000/7000/8000/9000/10000[2000/3000/4000/5000/6000/7000/8000/9000/10000]
# expected reduction factor in RMSE for sqrt(N) consistency[RMSE预期减少的因素SQRT（N）的一致性]
expexcted.rmsegr = sqrt(2000/seq(3000,10000,by=1000))
# actual RMSE reduction[减少实际RMSE]
actual.rmsegr = matrix(NA, ncol = 8, nrow = 6)
rownames(actual.rmsegr) = c("mu", "ar1", "ar2", "ma2", "ma2", "sigma")
# start at 2000 (window 1)[2000年开始（窗口1）]
rmse.start = as.data.frame(dist, window = 1, which = "rmse")
for(i in 2:nwindows) actual.rmsegr[,i-1] = as.numeric(as.data.frame(dist,
window = i, which = "rmse")/rmse.start)
par(mfrow = c(2,3))
for(i in 1:6){
plot(seq(3000,10000,by=1000),actual.rmsegr[i,], type = "l", lty = 2,
ylab = "RMSE Reduction", xlab = "N (sim)",main = rownames(actual.rmsegr)[i])
lines(seq(3000,10000,by=1000), expexcted.rmsegr, col = 2)
legend("topright", legend = c("Actual", "Expected"), col = 1:2, bty = "m",
lty = c(2,1))
}
## End(Not run)[＃（不执行）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-28 23:31:59
