R语言 rugarch包 ARFIMAroll-class()函数中文帮助文档(中英文对照)

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ARFIMAroll-class(rugarch)
ARFIMAroll-class()所属R语言包：rugarch

                                        class: ARFIMA Rolling Forecast Class
                                         类别：ARFIMA滚动预测类

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Class for the ARFIMA rolling forecast.
类的的ARFIMA滚动预测。


插槽----------Slots----------




roll: Object of class "vector"
roll：对象类"vector"的




forecast: Object of class "vector"
forecast：对象类"vector"的




model: Object of class "vector"
model：对象类"vector"的


扩展----------Extends----------

Class "ARFIMA", directly. Class "rGARCH", by class "ARFIMA", distance 2.
类"ARFIMA"，直接。类"rGARCH"“类”ARFIMA“，距离2。


方法----------Methods----------




as.ARFIMAforecast signature(object = "ARFIMAroll"):  extracts  and converts the forecast object contained in the roll object to one of ARFIMAforecast given the refit number supplied
as.ARFIMAforecastsignature(object = "ARFIMAroll")：提取并转换之一ARFIMAforecast给定数量的改装供给辊对象中包含的预测对象




as.data.frame signature(x = "ARFIMAroll"): extracts various
as.data.frame signature(x = "ARFIMAroll")：提取各种




fpm signature(object = "ARFIMAroll"):
FPMsignature(object = "ARFIMAroll")：




report signature(object = "ARFIMAroll"): roll backtest reports
报告signature(object = "ARFIMAroll")：卷回溯测试报告


注意----------Note----------

The as.data.frame extractor method allows the extraction of a variety of  values from the object. Additional arguments are:<br> which indicates the type of value to return. Valid values are &ldquo;coefs&rdquo;  returning the parameter coefficients for all refits, &ldquo;density&rdquo; for the  parametric density, &ldquo;coefmat&rdquo; for the parameter coefficients with their  respective standard errors and t- and p- values, &ldquo;LLH&rdquo; for the likelihood across the refits, and &ldquo;VaR&rdquo; 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 &ldquo;density&rdquo; or "VaR".<br> refit indicates which refit window to return the &ldquo;coefmat&rdquo;  if that is chosen. If &ldquo;series&rdquo; is chosen under via the which  argument, then the forecast series is returned for a particular refit, else  when &ldquo;all&rdquo; is used it returns the complete forecasted series across all  refits.<br> The report method takes the following additional arguments:<br> type for the report type. Valid values are &ldquo;VaR&rdquo; for the Value at  Risk report based on the unconditional and conditional coverage tests for VaR  exceedances (discussed below) and &ldquo;fpm&rdquo; 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.<br> The &ldquo;fpm&rdquo; does not take any additional arguments, but instead returns the forecast performance measures for all &ldquo;n.ahead&rdquo; values.
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：<BR>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。的<BR> n.ahead为的n.ahead的预测水平返回which带参数的“密度”或“VAR”。参考改装改装窗口返回“coefmat”，如果选择的。如果选择了“系列”下通过参数，然后返回一个特别改装的预测系列，否则当“所有”是用来返回完整的预测系列的所有整修。<BR>的report方法需要下列附加参数：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。的联合和单独的无条件测试报告，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。参考“FPM”不采取任何额外的参数，而是返回预测性能措施为所有“n.ahead的”的价值观。


（作者）----------Author(s)----------


Alexios Ghalanos

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


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