ugarchfilter-methods(rugarch)
ugarchfilter-methods()所属R语言包:rugarch
function: Univariate GARCH Filtering
功能:单变量GARCH过滤
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Method for filtering a variety of univariate GARCH models.
过滤各种单变量GARCH模型的方法。
用法----------Usage----------
ugarchfilter(spec, data, out.sample = 0, n.old=NULL, ...)
参数----------Arguments----------
参数:data
A univariate data object. Can be a numeric vector, matrix, data.frame, zoo, xts, timeSeries, ts or irts object.
一元数据对象。可以是一个数值向量,矩阵,数据框,动物园,XTS,时间序列,TS或IRTS对象。
参数:spec
A univariate GARCH spec object of class uGARCHspec with the fixed.pars argument having the model parameters on which the filtering is to take place.
一个单变量GARCH规范类的对象uGARCHspec的模型参数的过滤是发生在fixed.pars参数。
参数:out.sample
A positive integer indicating the number of periods before the last to keep for out of sample forecasting (as in ugarchfit function).
一个正整数,表示前的最后期间保持了样本外预测(如在ugarchfit功能)。
参数:n.old
For comparison with uGARCHfit models using the out.sample argument, this is the length of the original dataset (see details).
为了比较与uGARCHfit模型使用out.sample参数,这是原始数据集的长度(见详情)。
参数:...
.
。
Details
详细信息----------Details----------
The n.old argument is optional and indicates the length of the original data (in cases when this represents a series augmented by newer data). The reason for using this is so that the old and new datasets agree since the original recursion uses the sum of the residuals to start the recursion and therefore is influenced by new data. For a small augmentation the values converge after x periods, but it is sometimes preferable to have this option so that there is no forward looking information contaminating the study.
n.old参数是可选的,并且表示的长度的情况下的原始数据(若这代表了一系列增强由较新的数据)。使用这一点的原因是,使旧的和新的数据集的同意,因为原来的递归使用启动递归的残差的总和,因此,由新的数据的影响。对于一个小的增强后的值收敛X时期,但它有时是最好有此选项,以便有没有污染研究的前瞻性信息。
值----------Value----------
A uGARCHfilter object containing details of the GARCH filter.
AuGARCHfilter对象,其中包含的GARCH过滤器的详细信息。
(作者)----------Author(s)----------
Alexios Ghalanos
参见----------See Also----------
For specification ugarchspec, fitting ugarchfit, forecasting ugarchforecast, simulation ugarchsim, rolling forecast and estimation ugarchroll, parameter distribution and uncertainty ugarchdistribution, bootstrap forecast ugarchboot.
的规范ugarchspec,装修ugarchfit,预测ugarchforecast,模拟ugarchsim,滚动预测和估计ugarchroll,参数分布和不确定性ugarchdistribution,引导预测ugarchboot。
实例----------Examples----------
## Not run: [#不运行:]
data(sp500ret)
ctrl = list(RHO = 1,DELTA = 1e-8,MAJIT = 100,MINIT = 650,TOL = 1e-6)
spec = ugarchspec(variance.model = list(model = "eGARCH", garchOrder = c(1,1)),
mean.model = list(armaOrder = c(1,1), include.mean = TRUE),
distribution.model = "std")
egarch.fit = ugarchfit(data = sp500ret[,1,drop=FALSE], spec = spec,
solver = "solnp", solver.control = ctrl)
spec = ugarchspec(variance.model = list(model = "eGARCH", garchOrder = c(1,1)),
mean.model = list(armaOrder = c(1,1), include.mean = TRUE),
distribution.model = "std", fixed.pars = as.list(coef(egarch.fit)))
egarch.filter = ugarchfilter(data = sp500ret[,1,drop=FALSE], spec = spec)
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注:
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