uGARCHroll-class(rugarch)
uGARCHroll-class()所属R语言包：rugarch
class: Univariate GARCH Rolling Forecast Class
类别：单变量GARCH滚动预测类
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Class for the univariate GARCH rolling forecast.
一类为单变量GARCH滚动预测。
类对象----------Objects from the Class----------
A virtual Class: No objects may be created from it.
可能会从它创建一个虚拟类：没有对象。
扩展----------Extends----------
Class "GARCHroll", directly. Class "rGARCH", by class "GARCHroll", distance 2.
类"GARCHroll"，直接。类"rGARCH"，类的“GARCHroll”，距离2。
方法----------Methods----------
as.data.frame signature(x = "uGARCHroll"):
as.data.framesignature(x = "uGARCHroll")：
plot signature(x = "uGARCHroll", y = "missing"):
图signature(x = "uGARCHroll", y = "missing")：
report signature(object = "uGARCHroll"):
报告signature(object = "uGARCHroll")：
fpm signature(object = "uGARCHroll"):
FPMsignature(object = "uGARCHroll")：
as.uGARCHforecast signature(object = "uGARCHroll"): Extracts and converts the forecast object contained in the roll object to one of uGARCHforecast given the refit number supplied by
as.uGARCHforecastsignature(object = "uGARCHroll")：提取和转换的预测辊对象中包含的对象之一uGARCHforecast所提供的改装数量
show signature(object = "uGARCHroll"):
显示signature(object = "uGARCHroll")：
注意----------Note----------
The as.data.frame extractor method allows the extraction of a variety of values from the object. Additional arguments are: which indicates the type of value to return. Valid values are “coefs” returning the parameter coefficients for all refits, “density” for the parametric density, “coefmat” for the parameter coefficients with their respective standard errors and t- and p- values, “LLH” for the likelihood across the refits, and “VaR” for the Value At Risk measure if it was requested in the roll function call.<br> n.ahead for the n.ahead forecast horizon to return if which was used with arguments “density” or “VaR”.<br> refit indicates which refit window to return the “coefmat” if that was chosen.<br> The plot method takes the following additional arguments:<br> which allows for either a numeric value of 1:4, else will default to “ask” for interactive printing of the options in the command windows. Additionally, the value of “all” wil create a 2x2 chart with all plots.<br> n.ahead for the rolling n.ahead forecasts (defaults to 1).<br> VaR.alpha for the Value at Risk backtest plot, this is the tail probability and defaults to 0.01.<br> density.support the support for the time varying density plot density, defaults to c(-0.15, 0.15) but you should change this to something more appropriate for your data and period under consideration.<br> The report method takes the following additional arguments:<br> type for the report type. Valid values are “VaR” for the Value at Risk report based on the unconditional and conditional coverage tests for VaR exceedances (discussed below) and “fpm” for forecast performance measures.<br> n.ahead for the rolling n.ahead forecasts (defaults to 1).<br> VaR.alpha for the Value at Risk backtest report, this is the tail probability and defaults to 0.01.<br> conf.level the confidence level upon which the conditional coverage hypothesis test will be based on (defaults to 0.95).<br> Kupiec's unconditional coverage test looks at whether the amount of expected versus actual exceedances given the tail probability of VaR actually occur as predicted, while the conditional coverage test of Christoffersen is a joint test of the unconditional coverage and the independence of the exceedances. Both the joint and the separate unconditional test are reported since it is always possible that the joint test passes while failing either the independence or unconditional coverage test.
as.data.frame提取方法允许从对象中的各种值的提取。其他参数是：which表示返回值的类型。有效的值是“COEFS”返回参数系数可用于所有整修，“密度”为参数密度，“coefmat”与各自的标准误差和t为参数系数和p-值，“LLH”整个整修，风险度量的值，如果它被要求在辊函数调用和“var”的可能性。<BR> n.ahead为的n.ahead的预测水平，以返回which被使用参数“密度”或“var”。<BR>的refit改装窗口返回“coefmat”，如果选择的。<BR>的的绘图方法需要下列附加参数： <BR>允许的数值为1:4，否则将默认为“问”交互式打印命令窗口中的选项。此外，“所有”西港岛线的值创建一个2x2的线图的所有图。<BR> n.ahead的的滚动n.ahead预测（默认为1）。参考VaR.alpha的价值风险回溯测试的图这是尾概率默认为0.01。参考density.support密度曲线密度随时间变化的支持，默认为c（-0.15，0.15），但你应该改变的东西更适合于您的数据和期正在考虑之中。参考的报告方法采用下列附加参数：类型报告类型<BR>。有效的值是“风险价值”的风险价值报告的基础上无条件和有条件的风险值超标（见下文）和“FPM”的预测性能措施的覆盖测试。<BR> n.ahead滚动n.ahead预测（默认为1）。参考VaR.alpha的风险价值返回检验报告，这是尾概率，默认为0.01。参考conf.level将根据条件覆盖假设检验的置信水平（默认为0.95）。参考Kupiec无条件的覆盖测试看是否实际发生量的预期与实际超标的尾部VaR的概率预测，克里斯托弗的条件覆盖测试的是一个联合测试，无条件覆盖和的独立性超标。联合和独立的无条件的测试报告，因为它始终是可能的，而没有独立或无条件覆盖测试，联合测试通过。
（作者）----------Author(s)----------
Alexios Ghalanos
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。
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发表于 2012-9-28 23:40:14
