时间序列分析35习题

116解：1AR模型：tttxx11，且10^，3.0^1，9^，得tttxx13.07，9,0~Nt，96.1295.01Z,1.101tx，6.9tx(1)预测值的计算88.96.93.077)1(:11^ttxxt964.988.93.0717)2(:2^1^ttxxt9892.9964.93.0727)3(:3^1^ttxxt预测方差的计算：根据Green函数递推公式，算的10G3.013.0011GG09.03.03.0112GG则：91220GeVart81.99)3.01()(2222120GGeVart8829.99)09.03.01()(3222222120GGGeVartl步预测的95%的置信区间为leVarlxleVlxtttt96.1,ar96.1)(^^3x的95%的置信区间为8829.996.19892.9,9.882996.19892.9即1509.16,8275.3(2)5.101txt+1预测误差：62.088.95.101^11tttxx预测时期预测值lxt^新获得观察值修正预测1^1lxt19.8810.59.96415.1021^111^tttxGx9.9892045.1032^121^tttxGx2修正预测方差：9111tteVareVar81.9221tteVareVarl步预测的95%的置信区为leVarlxleVlxtttt1^11^196.1,ar96.1)(3tx的95%的置信区间为1839.16,9061.317解:datad17;inputx@@;time=_n_;cards;126.482.478.151.190.976.2104.587.4110.52569.353.539.863.646.772.979.683.680.760.37974.449.654.771.849.1103.951.682.483.677.879.389.685.558120.7110.565.439.940.188.771.48355.989.984.8105.2113.7124.7114.5115.6102.4101.489.871.598.355.566.178.4120.597110;procgplotdata=d17;plotx*time=1;symbol1c=redi=splinev=diamond;run;procarimadata=d17;identifyvar=xnlag=8minicp=(0:5)q=(0:5);estimatep=1;forecastlead=5id=timeout=results;run;procgplotdata=results;plotx*time=1forecast*time=2/overlay;symbol1c=redi=splinev=diamond;symbol2c=greei=joinv=star;run;（1）由输出结果可知，该序列平稳，且属于非白噪声序列。34（2）BIC信息量相对最小的是0,1ARMA模型,即1AR模型。参数估计结果显示各参数均显著。拟合模型的具体形式为：ttxB3148.01，即：tttxx13148.0（3）该城市未来5年的降雪量的预测结果518解：datad318;inputx@@;time=_n_;cards;0.970.451.611.261.371.431.321.230.840.891.181.331.210.980.910.611.230.971.100.740.800.810.800.600.590.630.870.360.810.910.770.960.930.950.650.980.700.861.320.880.680.781.250.791.190.690.920.860.860.850.900.540.321.401.140.690.910.680.570.940.350.390.450.990.840.620.850.730.660.760.630.320.170.46;procgplotdata=d318;plotx*time=1;symbol1c=bluei=joinv=star;run;procarimadata=d318;identifyvar=xnlag=8minicp=(0:5)q=(0:5);estimatep=1;forecastlend=5id=timeout=results;run;procgplotdata=results;plotx*time=1forecast*time=2l95*time=3u95*time=3/overlay;symbol1c=bluei=joinv=star;symbol2c=greeni=nonev=none;symbol3c=redi=joinv=none;run;6（1）由输出结果可知，该序列平稳，且属于非白噪声序列。（2）BIC信息量相对最小的是0,1ARMA模型,即1AR模型。参数估计结果显示各参数均显著。拟合模型的具体形式为：ttxB37235.01，即：tttxx137235.07（3）该地区未来5年的谷物产量的预测结果19解：datad319;inputx@@;time=_n_;cards;81.989.479.081.484.885.988.080.382.683.580.285.287.283.584.382.984.782.981.583.487.781.879.685.877.989.785.486.380.783.890.584.582.486.783.081.889.379.382.788.079.687.883.679.583.388.486.684.679.786.084.293.084.883.681.885.988.283.587.283.787.383.090.580.783.186.590.077.584.784.687.280.586.182.685.484.782.881.983.686.884.084.282.883.082.084.784.488.982.483.085.082.281.686.285.482.181.485.085.884.283.586.585.080.485.786.786.782.3886.482.582.079.586.780.591.781.683.985.684.878.489.985.086.283.085.484.484.586.285.683.285.783.580.182.288.682.085.085.285.384.382.389.784.883.180.687.486.883.586.284.182.384.886.683.578.188.881.983.380.087.283.386.679.584.182.290.886.579.781.087.281.684.484.482.288.980.985.187.184.076.582.785.183.390.481.080.379.889.083.780.987.381.185.686.680.086.683.383.182.386.780.2;procgplotdata=d319;plotx*time=1;symbol1c=redi=joinv=star;run;procarimadata=d319;identifyvar=xnlag=12minicp=(0:5)q=(0:5);estimateq=1;run;forecastlead=1id=timeout=results;run;9（1）由输出结果可知，该序列平稳，且属于非白噪声序列。（2）BIC信息量相对最小的是0,1ARMA模型,即1MA模型。参数估计结果显示各参数均显著。拟合模型的具体形式为：ttBx44063.01，即：144063.0tttx10（3）预测该序列下一时刻95%的置信区间为：1065.91,1925.80。