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我正在努力在 R 中重现 OxMetrics（Ox Professional 版本 7.10）的一些结果，但我很难弄清楚我在 R 中得到了正确的规范。我不希望得到相同的估计，但应该有一些相似的估计是可能的（有关 OxMetrics 和 R 的估计，请参见下文）。

这里的任何人都可以帮我弄清楚我如何做 OxMetrics 在 R 中所做的事情吗？

我试过使用forecast::arfima, forecast::Arima,fracdiff::fracdiff和arfima::arfima到目前为止，我最接近后者。

下面是数据和代码，

打击结果来自使用最大似然估计的 OxMetrics ARFIMA(2,0,2) 模型和使用包中的 R arfima（arfima代码打击较长的数据字符串）。

           OxMetrics         R (using arfima()]
AR         1.41763           1.78547    
AR        -0.51606          -0.79782 
MA        -0.89892          -0.08406
MA         0.30821           0.48083
Constant  -0.09382          -0.09423

y <- c(-0.0527281830620101, -0.0483283435220523,
-0.0761110069836706, -0.0425588714546148,
-0.0629789511239869, -0.118944956578757, 
-0.156545103342326, -0.138106089421937,
-0.107335059908618, -0.145013381825552, 
-0.100753517322066, -0.0987268545186417,
-0.0454663306471916, -0.0404439816954447,
-0.110574863632305, -0.0933955365797221,
-0.0915045759209185, -0.110397691370645,
-0.0944201704700927, -0.121257467376357,
-0.109785472344257, -0.0890776818684245, 
-0.0554059943242384, -0.0700566531543618,
 -0.0366694695635905, -0.0687369752462432,
-0.0651380598746858, -0.134224646388692, 
-0.0670924768348229, -0.0835771023087037,
-0.0709997877276756, -0.116003735777656,
-0.0794873243023737, -0.067057402058551, 
-0.0698663891865543, -0.0511133873895728,
-0.0513203609998669, -0.0894001277309737,
-0.0398284483421012, -0.0514468502511471, 
-0.0599700163953942, -0.0661889418696937,
-0.079516218903545, -0.0685966077135509,
-0.0861445337428064, -0.0923966209966709, 
-0.133444703431511, -0.131567692883267,
-0.127157375630663, -0.136327904368355, 
-0.102133208996487, -0.109453799095327,
-0.103333580486325, -0.0982528240902063, 
-0.139243862997714, -0.112067682286408,
-0.0741501704478233, -0.0885574830826608,
-0.0819203358523941, -0.0891168040724528, 
-0.0331415164887199, -0.038039022334333,
0.000471320939768205, -0.0250547289467331,
-0.0411983586070352, -0.0463752713008887, 
-0.0184870766950889, -0.0318185253129144,
-0.0623828610377037, -0.0718563679309012,
-0.0635702270765757, -0.0929728977267059, 
-0.0894248292570765, -0.0919046741661464,
-0.0844700793317346, -0.112800098282505,
-0.141344968548085, -0.127965917566584,
-0.143980868315393, -0.154901662762077,
-0.130634570152671, -0.150417664726561,
-0.163723312802416, -0.146099566906346,
-0.14837251795191, -0.144887288973472,
-0.14232221415307, -0.142825446351853,
-0.158838097005599, -0.14340614330986,
-0.118935233992604, -0.109627188482776,
-0.120889714109902, -0.119484146944083,
-0.0950435556738212, -0.134667374330086,
-0.155051119642286, -0.134094795193097,
-0.128627607285988, -0.133954472488274,
-0.119286541395138, -0.135714339904381,
-0.0903767618937357, -0.109592987693797,
-0.0770998518949151, -0.108375176935532, 
-0.136901231908067, -0.0856673865524131,
-0.108854388315838, -0.0708359081737591,
-0.106961434062811, -0.0429126711978416, 
-0.0550592121225453, -0.0715845951018634,
-0.0509376225313689, -0.0570175197192393,
-0.0724229547086495, -0.0867303057832318, 
-0.089712447506396, -0.125158029708487,
-0.122260116350003, -0.0905629436620448, 
-0.090357598491857, -0.097173095034008,
-0.0674973361276239, -0.12411935716644,
-0.0957789729967162, -0.088838044599159,
-0.110065127067576, -0.108172925482296)

# install.packages(c("arfima"), dependencies = TRUE)
# library(arfima)
arfima::arfima(y, order = c(2, 0, 2))
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1 回答 1

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解决方法是将numeach选项中的第二个参数设置为0，即

arfima::arfima(y, order = c(2, 0, 2), numeach = c(2, 0))

这控制小数参数的启动次数。

于 2016-10-07T02:15:50.263 回答