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1、SUMMARY OUTPUT回歸統(tǒng)計Multiple R 0.668509R Square 0.446904Adjusted R Square0.407397標準誤差 4642.289觀測值16方差分析dfSSMSF Significance F回歸分析1 2.44E+08 2.44E+08 11.31207 0.004639殘差14 3.02E+08 21550848總計15 5.45E+08Coefficients 標準誤差t StatP-value Lower 95%Upper 95%下限 95.0%上限 95.0%Intercept-751.642 2887.059-0.26035 0
2、.798385-6943.77 5440.482-6943.77 5440.482X Variable 1846.7665 251.7635 3.363341 0.004639 306.7876 1386.745 306.7876 1386.745上限 95.0%SUMMARY OUTPUT回歸統(tǒng)計Multiple R 0.391145R Square 0.152994Adjusted R Square0.105939標準誤差16540.2觀測值20方差分析dfSSMSF Significance F回歸分析1 8.89E+08 8.89E+08 3.251335 0.088132殘差18 4
3、.92E+09 2.74E+08總計19 5.81E+09Coefficients 標準誤差t StatP-value Lower 95%Upper 95%下限 95.0%上限 95.0%Intercept-2076.83 7683.444-0.2703 0.790005-18219.1 14065.49-18219.1 14065.49X Variable 11156.541 641.4015 1.803146 0.088132-190.994 2504.075-190.994 2504.075上限 95.0%透明塑料的需求量與誤差分析時期實際需求量 剔除季節(jié)性影響后的需求Dt=847t-7
4、51St=Dt/Dt季節(jié)性需求季節(jié)性需求靜態(tài)方法SHEET 4132009633.3311.69276589438.123.97344204472.2517902.471.47423844656.7526370.900.51536544981.37534841.05686805124.37543312.00759955206.551781.16819535966.62560250.32947426671.37568720.691013673685077191.77116640679185660.781227376573.12594130.291334866363.25102600.341413
5、1866307.75111071.191554486931.5119540.461634857887.375128010.2717772817927.125136480.57181659127520.125144951.141982361153425.37203316161890.2021 Dt=847t-75122232425262728293031324期移動平均法時期實際需求量 移動平均值13200 需求水平2765834420423844415.5536544529686804784.5759955178.25819535070.5947425342.510136736590.7511
6、664067521227376948133486663414131866512.251554486214.251634856401.251777287461.7518165918313198236127541.2520331627499212223242526272829303132時期實際需求量 需求水平預測需求單一指數平滑法阿爾法=0.1010066.85132009380.16510066.85276589207.94859380.165344208729.153659207.9485423848094.6382858729.15365536547650.5744578094.63828
7、5686807753.5170117650.574457759957577.665317753.517011819537015.1987797577.66531947426787.8789017015.19877910136737476.3910116787.8789011166407392.751917476.3910111227376927.1767197392.751911334866583.0590476927.17671914131867243.3531426583.0590471554487063.8178287243.3531421634856705.9360457063.817
8、8281777286808.1424416705.93604518165917786.4281976808.142441198236115243.885387786.42819720331614051.0968415243.88538211405122140512314051241405125140512614051271405128140512914051301405131140513214051時期實際需求量 需求水平L需求趨勢T預測需求需求趨勢和季節(jié)性需求修正后的指數平滑法（winter）阿爾法=0.1，貝塔=0.1，伽馬=0.10-75184713200767.2510638914.1
9、251064 1122.309611.69276583142.6002551060.247515 1143.33583.97344204722.9885251112.26159 6167.27881.47423845758.9591461104.632493 2954.53320.51536546954.6792841113.741258 80240.361686809108.3869991217.737904 31995.0277599510569.044331242.029846 15152.6058195311045.498671165.472296 5980.2425947421199
10、8.810041144.256203142755.1101367314737.908561303.740434 52118.349 11664015850.250051284.60054 23539.59212273716003.705951171.486077 8675.803813348616199.374961073.904369 200790.44141318618351.483311181.724768 68496.55815544818739.03621102.30758 29115.28216348518598.69877978.0430787 9912.194517772819
11、263.32298946.7011922228866.3181659121719.021761097.60095 80142.112198236138058.577462621.796426 59694.57420331637317.868412285.54587820052.221 Dt=-751+847t200790.442272753.0812328641.0472410475.68825255572.532691335.0222735517.2242812848.29929310354.6130109916.963142393.4013215220.91時期實際需求量 需求水平需求趨勢
12、預測需求趨勢修正后的指數平滑法（holt）阿爾法=0.1，貝塔=0.1sheet 50-2076115713200-507.11198.19-919276581387.7811267.8591691.09344202832.076091285.502699 2655.6401423843944.220911268.166911 4117.5788536545056.5490391252.583033 5212.3878686806546.2188651276.291712 6309.1321759957639.7595191258.016606 7822.5106819538203.29851
13、31188.568845 8897.7761947428926.8806221142.070172 9391.8674101367310429.355711178.110664 10068.95111664011110.719741128.436 11607.46612273711288.940171033.414442 12239.15613348611438.71915945.0508964 12322.355141318612463.99304953.073195912383.7715544812620.15961873.3825336 13417.06616348512492.6879
14、3773.2971121 13493.54217772812712.18654717.9172617 13265.985181659113746.19342749.5262237 13430.104198236121282.247681428.17902714495.7220331620770.984041234.23476 22710.42721 Dt=-2076+1157t12322.3552213355.7692314389.1832415422.5982516359.1732617132.4712717905.7682818679.0652931879.0973033113.33231
15、34347.5663235581.801透明塑料預測需求的誤差預測方法MADMAPE（%）TS的變動范圍四期移動平均法9038.015625 100.54957低估單一指數平滑法7998107.50765（-6，+6）以外Holt模型8679139.28946高估Winter模型46505853.7559高估靜態(tài)方法的路徑系數在+6以外，會高估需求結論：采用？模型2001年第一季度2001年第二季度2001年第三季度2001年第四季度2002年第一季度2002年第二季度2002年第三季度2002年第四季度2003年第一季度2003年第二季度2003年第三季度2003年第四季度誤差誤差的的標準差
16、預測值E=預測值-需求值At=ABS(E)MSEMADE/D1122-2078207843167974316797207864.927833739-39193919153551759835986299851.16962627-1793179332160887629354259740.573431335-1049104911000255997021221043.99416407303707637076137466575427973076891831014.682171748494849472155207245134841906897.8620175981603160325703202104827
17、67800226.742653051109810981204744184323014713956.201148033975597755975714855124798826582147451594.19430609169361693628684205974762812914964123.86761257059305930351623996828585181414389.3040547662029202941169936262967241313474.13363119947116461116461135631264171621437470210823340.81644044308583085895
18、2240995157363772121780234.024175411209312093146249271147847849121134221.9779648129962996897881313866347612000185.98183159555151827151827230514415782661035162277551964.6355747940888408881671860637260608102228485246.449222513-5984859848358179222726574342433013672.66555819748814881238231462525753689288
19、73147.1923199163誤差的標準差36090.9770914274849912238771843493245611628278380977843742813343預測值FE=預測值-需求值At=ABS(E)MSEMADE/D%4415.5761.5761.5579882.25579882.25761.5 20.840184529-41514151172308018905341.6252456.25 47.822584784.5-1210.51210.51465310.256425331.1672041 20.191835178.253225.253225.2510402237.567
20、419557.766 2337.063 165.14345070.5328.5328.5107912.255957228.6631935.35 6.9274575342.5-8330.58330.569397230.2516530562.26 3001.208 60.926646590.75-49.2549.252425.562514169399.882579.5 0.7417176752401540151612022514413253.02 2758.938 146.69356948346234621198544414143496.46 2837.056 99.311536634-65526
21、5524292870417022017.213208.55 49.689066512.251064.251064.251132628.06315577527.29 3013.614 19.534696214.252729.252729.257448805.56314900133.81 2989.91778.31426401.25-1326.751326.751760265.56313889374.72 2861.981 17.168097461.75-9129.259129.2583343205.5618850362.63 3309.643 55.025318313-7404874048548
22、3106304383134092.1 8025.533 89.9066327541.2524225.2524225.25586862737.6395867132.4 9038.016 730.556427499誤差的標準差11297.522749927499274992749927499274992749927499274992749927499E=預測需求-需求值At=ABS(E)MSEMADE/D6867686747153629471536296867214.589117221722296585225059741429522.48844478847882292445124347977445
23、9108.32466345634540260975283262274931266.15584441444119719268266048354833121.5281-10291029105971722347315419911.8597417591759309238219596611385029.333065625562531636860211016424072288.001322732273516743319331174387247.93755-688568854740489322138546417350.355683683669955020189546387012.59625465646562
24、1676026203134203935170.1042344134411184169719661749389798.71419-660366034359882921371540409150.0753917951795322329320161657393832.954353579357912807937197020493915102.692-10221022104461518604553374513.22547-978397839570430222887873408158.96485-74575745755561366760314386761779190.54598119281192814227
25、44503057811467998359.707誤差的標準差9996.968E=預測需求-需求值At=ABS(E)MSEMADE/D-2078207843167974316797207864.92783-651565154244085023378824429685.0700517471747305298316603543344739.5311957157132550812534035272823.93176765867658658654706871183121365174992095.962331523315543590466107653288218469268.606391589158838
26、6172693472271717138152.754402740271621868381990971315500206.208138013138013190476160652845210418291122910.44138445384451478044827270849385930045281.17711690016900285596211248823043728850254.51195939593935269391228381701626941216.9822197304197304389290433705102680582400465659.909553115531130592577734
27、95672181041136419.46432366723667560140249466361637239972434.42156427642741308829437472215137875184.4245221138221138489021483156993982514486552861.5263551635514038743814682980258649483383.0457-226662266651376686164973796534807227.520821673616736280100395618651569046505504.7105誤差的標準差58130.92E=預測需求-需求值
28、At=ABS(E)MSEMADE/D-4119411916966161169661614119128.7188-696769674853783532751998554390.97558-17641764311296622872321428339.9176417341734300529517905564364672.7172315581558242857314810166322842.64882-23712371562101513278641308627.3141518281828333979511858806290630.483916945694548229915164051943411355
29、.5953465046502162126616984758354898.05709-360436041298917116585199355426.35888496749672467572217320701368274.811249502950290290964234015564167347.17418836883678081163276076804527253.4812-8028026435732568167242616.0839527969796963506017282032954508146.27511000910009100170916327012724852287.1892553855
30、383066927832581743489271.6613-31613161999126531326716479619.05187-67865678654605696278272083009811582.3997819394193943761437872772860488679584.8741誤差的標準差10848.98MAPEbiasTS=bias/MAD64.92783-2078-158.04871-5996-252.22362-7790-350.16625-8838-4243.0694282383.07504256218.8682367324.05068187191.4217383364
31、.79088904174.5191394335.52382429332.26071150307.80117961311.42141319668.8187338291.22891378969.75013457273.137713992510.6540646509.112925638612.1615098489.463728724413.1883942471.631329933814.1635947447.528230233415.1161882536.769845416116.3631154520.640949505017.3794288497.063243520214.44149479.569
32、744008215.2421268高估MAPE%biasTS=bias/MAD20.84018761.5134.33138-3389.5-1.379949129.61819-4600-2.253797263.49949-1374.75-0.588238452.18508-1046.25-0.540599953.64201-9376.75-3.124324946.08482-9426-3.654196558.6609-5411-1.961262363.17764-1949-0.686979961.82878-8501-2.649483457.98387-7436.75-2.467718559.6
33、7806-4707.5-1.574458656.40806-6034.25-2.108417456.30929-15163.5-4.581612258.54912-89211.5-11.115959100.5496-64986.3-7.1903228低估MAPEbiasTS=bias/MAD214.589168671118.538885892115.134133773153197224147241635124.1576231335.50964521110.6113248926.46524733132.785305177.49437836123.3575327908.46828051116.05
34、73259056.20711807106.6518267416.90980214111.9395313977.97785502110.9221348388.93861485106.576282356.90221666102300307.62638722102336098.5841460996.5256325878.7013277194.43889228045.5885814994.234-51770-6.6451341107.5077-39842-4.9818189MAPEbiasTS=bias/MAD64.92783-2078-174.99894-8592-263.17636-6845-1.
35、986069253-6275-2.3004388462703124.01797764429.6711936275.06951711390.11151027845.99730093367.12361068126.89127691649.71442448258.40970697612.86072832709.42804354580.283530017010.4043512550.008430610911.3621379943.077750341312.5708755905.676755872413.582249687458239114.570078183158881815.5462803950.5
36、78980995616.6468074919.049387350717.6527142872.126785084117.6994881853.755986757718.6556733高估MAPEbiasTS=bias/MAD128.7188-4119-1109.8472-11086-286.53733-12850-383-11117-3.049041875-9558-2.960650267.0487-11929-3.866181861.82515-10102-3.476375998.54642-3157-0.925589798.4920514930.4207526891.27874-2111-0.594008989.7816928560.77568261111.2311123592.96552375122.1734211954.68234349113.8813175364.11597915116283626.29174377127383707.90883929123.4978439088.97562242117.6953407478.49651039115.8376-27118-3.341608139.2895-7723-0.8898849高估
案例 透明塑料
