我正在尝试使用rcaller通过R集成来预测java中的一些数据。类似于rcaller（https://github.com/jbytecode/rcaller/blob/master/RCaller/src/main/java/examples/ForecastExample.java）
中的代码示例从r读取结果并打印上部，下部，拟合和平均值（我使用tt $ mean添加）。以下是示例值：
R命令和值：
> lst<-forecast(arfima(ma(meta1, order=7)),h=10)
> lst$mean
Time Series:
Start = 105
End = 114
Frequency = 1
[1] 144.3219 137.5436 131.7407 126.7097 122.3315 118.5163 115.1900 112.2892
[9] 109.7589 107.5511
> lst
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
105 144.3219 122.37756 166.2663 110.76091 177.8830
106 137.5436 107.51843 167.5687 91.62408 183.4631
107 131.7407 96.49639 166.9850 77.83919 185.6422
108 126.7097 87.82406 165.5954 67.23922 186.1803
109 122.3315 80.81365 163.8493 58.83544 185.8275
110 118.5163 75.05634 161.9762 52.05005 184.9825
111 115.1900 70.27757 160.1024 46.50237 183.8776
112 112.2892 66.27976 158.2986 41.92383 182.6546
113 109.7589 62.91454 156.6032 38.11664 181.4011
114 107.5511 60.06726 155.0349 34.93086 180.1713
Java xml结果：
Available results from ts() object:
<?xml version="1.0"?>
<root>
<variable name="upper" type="numeric" n="10" m="2"><v>0.0415022799211068</v><v>0.0591474942854589</v><v>0.0614232201188155</v><v>0.0614270046751282</v><v>0.0614250367195549</v><v>0.0614268906025606</v><v>0.0614267754071175</v><v>0.061426764426567</v><v>0.0614267887421146</v><v>0.0614268038998227</v><v>0.0630097192924167</v><v>0.089534103213086</v><v>0.0928426957181002</v><v>0.0928794445803825</v><v>0.0928775168539632</v><v>0.0928794017875694</v><v>0.0928792867199118</v><v>0.0928792757404699</v><v>0.0928793000618265</v><v>0.0928793152218208</v></variable>
<variable name="lower" type="numeric" n="10" m="2"><v>-0.0397547602668397</v><v>-0.0556558470226343</v><v>-0.0572823843642995</v><v>-0.057403141920541</v><v>-0.0574052618654761</v><v>-0.0574035252944317</v><v>-0.0574036409726598</v><v>-0.057403651957399</v><v>-0.0574036276637981</v><v>-0.0574036125147275</v><v>-0.0612621996381496</v><v>-0.0860424559502614</v><v>-0.0887018599635842</v><v>-0.0888555818257953</v><v>-0.0888577419998844</v><v>-0.0888560364794405</v><v>-0.0888561522854541</v><v>-0.088856163271302</v><v>-0.08885613898351</v><v>-0.0888561238367256</v></variable>
<variable name="mean" type="numeric" n="10" m="1"><v>0.000873759827133541</v><v>0.00174582363141232</v><v>0.00207041787725797</v><v>0.00201193137729362</v><v>0.0020098874270394</v><v>0.00201168265406443</v><v>0.00201156721722883</v><v>0.00201155623458396</v><v>0.00201158053915825</v><v>0.00201159569254763</v></variable>
</root>
结果是否缩放？ 如果是这样如何获得实际数据？