x0φ100.8t01234567891011121314151617x00.566019283-1.009956915-0.868955196-0.448367776-0.9649272980.1881231321.208361714-0.343774999-0.226854018-1.613917897-1.397239031-1.820807534-3.864614286-3.640608696-3.713235953-2.808985619-2.95657419AR(1)模型:xt118xt1-0.681021086t其中:10.8,x00,t~WN(0,1)202122232425260191.0562114913.9002298652.8940457752.6155702754.300190061.7681597940.8957695081.2928325741.7975073711.3367774055432序列值x127-128-2-3-4-5293031320510-0.362711296-0.560448748-0.061797902-0.520691083153334353637383940-0.076585513-0.867638177-0.852805579-1.009081858-2.232978319-2.211276882-0.615831998-0.90452371920253041424344454647484950515253545556575859606162631.5505425920.2130226292.0995924261.2175762970.627227738-0.2003507891.5192579180.667129559-0.0666481450.049620415-0.610225642-2.046224358-1.01351103-0.5159880640.076260763-1.4021554980.3560015430.7903881450.5531559131.3325714430.1157999540.578352731.62436189564656667686970717273747576777879808182838485861.2462594161.7502828181.0893192580.094486512-1.015189316-1.440488815-0.372967155-0.4503762090.042611423-0.282643192-1.905959003-3.206337365-3.386279716-2.450982529-2.599488541-2.074796148-0.2497850580.314016703-0.699408053-0.502160741-0.4524597521.050487179-0.296236719878889909192939495969798991000.6187972551.1996612822.4145266711.1070686950.912156777-0.490351653-1.876324142-1.459794274-0.556482817-1.90559837-2.85818917-1.369247833-0.447202614-0.874424452基于样本的总体均值估计延迟k=1的总体方差估计延迟k=1的自协方差函数估计延迟k=1的自协相关函数估计-0.264199552.140405361.57801450.737250303延迟k=0的自协相关函数估计延迟k=1的自协相关函数估计延迟k=2的自协相关函数估计延迟k=3的自协相关函数估计延迟k=4的自协相关函数估计延迟k=5的自协相关函数估计延迟k=6的自协相关函数估计延迟k=7的自协相关函数估计延迟k=8的自协相关函数估计延迟k=9的自协相关函数估计延迟k=10的自协相关函数估计延迟k=11的自协相关函数估计延迟k=12的自协相关函数估计10.7372503030.5937345660.4748965050.3848049880.3682922450.2462231460.2547259540.2382028220.1779814040.0958256050.082376310.001836832平稳时间序列WN(0,1)303540455055606570758085时间tx0φ10-0.8t01234567891011121314151617x0-1.3749524271.122481125-0.109935177-0.4752614551.920839359-1.1086829490.8205683480.098392275-0.336332668-0.1461547471.754491993-0.7898128062.875017146-3.3896597673.36073526-2.4428959061.665567129AR(1)模型:xt1xt1t其中:10.8,x00,t~WN(0,18-2.386055336AR(1)模型:xt1xt1t190.814439819其中:0.8,x0,~WN(0,10t20-0.98677340421222324541.235176224-1.8658292533.625305766-3.15781665521序列值x2526270.969827053-0.85653483500.373785459-12829303132859095100-1.207826752-20.594442829-30.107939746-40.760516205-51.048501639-0.983188790.01374110105103334353637383940-1.0845871060.698912998-0.1814583430.858879538-2.4114838651.8601702774142434445464748495051525354555657585960616263-1.7249471850.0948268320.083957408-1.044922447-0.1162155770.716073751-2.1449241750.701608324-1.8191482731.3923055710.0493362871.23036421-0.218450968-0.762761406-0.006531211-1.0315597970.704441095-2.4082943720.8641646411.43104872-1.666971575-1.115011084-0.42297577864656667686970717273747576777879808182838485860.5812309430.1271925711.092236570.47911186-1.704927531.824469477-1.4417764540.73211464-0.6768069410.765642561-1.798473024-0.7667795850.425141509-0.481856990.0420737610.199102439-0.032355688-1.0696231951.2042247480.2861898862.363257048-1.2099636480.188928728878889909192939495969798991000.078099327-0.2011281070.6363448590.145053721-1.7926263161.217088495-0.4145203960.537497547-0.030223842-2.0967457862.057030262-0.732574469-0.4103663510.508689501基于样本的总体均值估计延迟k=1的总体方差估计延迟k=1的自协方差函数估计延迟k=1的自协相关函数估计-0.0313770112.463990812-1.895964-0.769468778延迟k=0的自协相关函数估计延迟k=1的自协相关函数估计延迟k=2的自协相关函数估计延迟k=3的自协相关函数估计延迟k=4的自协相关函数估计延迟k=5的自协相关函数估计延迟k=6的自协相关函数估计延迟k=7的自协相关函数估计延迟k=8的自协相关函数估计延迟k=9的自协相关函数估计延迟k=10的自协相关函数估计延迟k=11的自协相关函数估计延迟k=12的自协相关函数估计1-0.7694687780.448845319-0.3346658510.229079378-0.2179820960.25570847-0.2696323710.2624515470.4488453190.4488453190.4488453190.448845319xt1xt1t0.8,x00,t~WN(0,1)xt1xt1t平稳时间序列0.8,x00,t~WN(0,1)1015202530354045505560时间t65707580859095100