2016-07-24T08:15:55.362000000P0D1LibreOfficeDev/5.3.0.0.alpha0$Linux_X86_64 LibreOffice_project/7e1fd9aa86ab8d5e86f35df8615f438a3383af98 0 0 22009 4420 view1 2 8 0 0 0 0 2 0 0 0 0 0 75 60 true false 2 44 0 0 0 0 2 0 0 0 14 0 75 60 true false Sheet2 1857 0 75 60 false true true true 12632256 true true true true false false false 1270 1270 1 1 true false 7 false false true true false false false 1270 1270 true true true true true true true false 12632256 false Generic Printer cs CZ de DE en US nl NL 3 1 true 1 true 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 false 0 Kč - Kč ( ) - Kč - Kč Kč - Kč Kč - Kč Kč - Kč £ - £ £ - £ £ - £ £ - £ £ - £ ( ) ( ) £ - £ £ - £ € - € - € / / / / € - € Kč - Kč Kč - Kč Kč - Kč Kč - Kč - - - - - - Kč - Kč - Kč - - Kč - Kč - Kč : : : : Yes Yes No True True False On On Off ¥€ ( € ) € - € $ ($ ) € - € € - € € - € € - € - - € - € - € - - € - € - € $ ($ ) $ ($ ) $ ($ ) ( ) - $ $ ( ) $ - $ $ ( ) $ - € ( € ) \ \- \ \- \ \- \ \- \ \ - \ - - - \ \ - \ - - - - - - - $ $( ) $- ( ) - $ $( ) $- ( ) - % % % % % % % % % % € - € € - € € - € € - € € - € € - € € - € € - € € - € € - € € - € € - € € - € € - € € - € % % % % % % $ ( $ ) % % - % - - - £ - £ £ - £ % - % DM - DM DM - DM DM - DM DM - DM - - DM - DM - DM - - DM - DM - DM Ouch! - - Error detected! - Result=0 - No Errordetection / / / / ( ) - $ $ ( ) $ - ( ) - $ $ ( ) $ - £ -£ £ -£ £ -£ £ -£ - - £ -£ £ - - - £ -£ £ - ￥ - ￥ DM - DM DM - DM DM - DM DM - DM DM - DM € € - tan aa / / - - - - : : : : : : / / : ( ) ( ) ( ) ( ) ( ) ( ) - : : : ( ) % ( ) - ( ) - ( ) - ( ) - . . : : : . . : - - - - € - € € - € € - € € - € € € - € € - € € - € € - - - - - - - : : : : : : - - : - - - - - - € € - € - - - € € - € - % / / ??? Page 1 ??? (???) 00/00/0000, 00:00:00 Page 1 / 99 FORECAST.ETS.MULT Function Result TRUE Sheet Result Description 1 TRUE Simple FORECAST.ETS.MULT formulas with local references and values Function Expected Correct FunctionString Comment 1 2 Known Y Known X 2 125.2 B C E 9 periods 1 1 11.908196123559 11.908196123559 TRUE =FORECAST.ETS.MULT(6, N1:N5, M1:M5) https://bugs.documentfoundation.org/show_bug.cgi?id=94635 2 4 6 20 4 118.9 target 34 46 49 2002 34 2 46 2 #VALUE! #VALUE! TRUE =FORECAST.ETS.MULT(30,P2:P6,Q2:Q6) 3 7 7 28 6 106.0 seasonality 4 1 jaar 12 date sales 4 1 jaar 4 1 jaar 3 12 1 jaar 3 sales 125.226808384339 125.226808384339 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 4 8 9 31 4 118.9 datacompletion 1 1 1 01/01/01 3 240 325 1 1 4 1 4 1 3 240 325 118.933231648245 118.933231648245 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 5 11 15 38 5 111.5 aggregation 1 1 2 02/01/01 2 741 349 48.4 1 1 1 5 1 5 2 2 741 349 48.4 1 105.954105316101 105.954105316101 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 21 40 6 106.0 3 03/01/01 2 987 427 48.5 2 2 125.2 6 6 3 2 987 427 48.5 2 118.933231648245 118.933231648245 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 7 105.0 4 04/01/01 3 456 892 57.45 3 period sales 4 118.9 7 7 4 3 456 892 57.45 3 111.549667344589 111.5496673445890000000 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 8 109.5 01/01/01 1 41.7 1 112 5 05/01/01 3 740 738 64.95 4 1 362 6 106.0 1 41.7 8 1 112 8 5 3 740 738 64.95 4 105.954105316101 105.954105316101 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 9 117.5 04/01/01 2 24 2 118 6 06/01/01 3 979 178 62.55 5 2 385 4 118.9 2 24 2 118 6 3 979 178 62.55 5 105.026989677408 105.026989677408 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 10 125.6 07/01/01 3 32.3 3 132 7 07/01/01 4 160 454 60.15 6 3 432 5 111.5 3 32.3 3 132 7 4 160 454 60.15 6 109.479384966668 109.479384966668 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 11 130.2 10/01/01 4 37.3 4 129 8 08/01/01 4 162 013 69.25 7 4 341 6 106.0 4 37.3 4 129 8 4 162 013 69.25 7 117.5 117.5 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 12 129.3 01/01/02 5 46.2 5 121 9 09/01/01 3 809 132 68.6 8 5 382 7 105.0 5 46.2 5 121 9 3 809 132 68.6 8 125.584893794301 125.584893794301 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 13 123.6 04/01/02 6 29.3 6 135 10 10/01/01 3 794 419 65.05 9 6 409 8 109.5 6 29.3 6 135 10 3 794 419 65.05 9 130.169971873195 130.169971873195 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 14 115.9 07/01/02 7 36.5 7 148 11 11/01/01 3 719 219 64.4 10 7 498 9 117.5 7 36.5 7 148 11 3 719 219 64.4 10 129.305702305035 129.305702305035 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 15 110.1 10/01/02 8 43 8 148 12 12/01/01 3 812 981 56.45 11 8 387 10 125.6 8 43 8 148 12 3 812 981 56.45 11 123.587140712742 123.587140712742 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 16 109.1 01/01/03 9 48.9 9 136 13 01/01/02 3 480 451 48 12 9 473 11 130.2 9 48.9 9 136 13 3 480 451 48 12 115.895758280092 115.895758280092 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 17 113.7 04/01/03 10 31.2 10 119 14 02/01/02 3 183 133 53.583 13 10 513 12 129.3 10 31.2 10 119 14 3 183 133 53.583 13 110.064393884398 110.064393884398 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 18 122.0 07/01/03 11 37.7 11 104 15 03/01/02 3 764 529 48.018 14 11 582 13 123.6 11 37.7 11 104 15 3 764 529 48.018 14 109.083826188552 109.083826188552 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 19 130.4 10/01/03 12 40.4 12 118 16 04/01/02 3 500 189 62.116 15 12 474 14 115.9 12 40.4 12 118 16 3 500 189 62.116 15 113.690130542309 113.690130542309 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 20 135.1 01/01/04 13 51.2 13 115 17 05/01/02 3 389 811 67.681 16 13 544 15 110.1 13 51.2 13 115 17 3 389 811 67.681 16 122 122 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 21 134.2 04/01/04 14 31.9 14 126 18 06/01/02 4 348 789 66.78 17 14 582 16 109.1 14 31.9 14 126 18 4 348 789 66.78 17 130.37414821866 130.37414821866 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 22 128.2 07/01/04 15 41 15 141 19 07/01/02 4 442 455 70.066 18 15 681 1 17 113.7 15 41 15 141 19 4 442 455 70.066 18 135.11313536205 135.11313536205 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 23 120.2 10/01/04 16 43.8 16 135 20 08/01/02 4 593 383 71.073 19 16 557 2 18 122.0 16 43.8 16 135 20 4 593 383 71.073 19 134.195413736738 134.195413736738 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 24 114.2 01/01/05 17 55.6 17 125 21 09/01/02 4 029 783 76.691 20 17 628 3 19 130.4 17 55.6 17 125 21 4 029 783 76.691 20 128.241049777238 128.241049777238 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 25 113.1 04/01/05 18 33.9 18 149 22 10/01/02 4 211 211 66.992 21 18 707 4 20 135.1 18 33.9 18 149 22 4 211 211 66.992 21 120.241849215595 120.241849215595 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 26 117.9 07/01/05 19 42.1 19 170 23 11/01/02 3 854 682 61.533 22 19 773 5 21 134.2 19 42.1 19 170 23 3 854 682 61.533 22 114.174682452695 114.174682452695 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 27 126.5 10/01/05 20 45.6 20 170 24 12/01/02 3 554 831 62.275 23 20 592 6 22 128.2 20 45.6 20 170 24 3 554 831 62.275 23 113.140662699697 113.140662699697 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 28 135.2 01/01/06 21 59.8 21 158 25 01/01/03 3 488 309 51.675 24 21 627 7 23 120.2 21 59.8 21 158 25 3 488 309 51.675 24 117.90087611795 117.90087611795 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 29 140.1 04/01/06 22 35.2 22 133 26 02/01/03 3 270 444 60.146 25 22 725 8 24 114.2 22 35.2 22 133 26 3 270 444 60.146 25 126.5 126.5 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 30 139.1 07/01/06 23 44.3 23 114 27 03/01/03 3 709 943 56.434 26 23 854 25 113.1 23 44.3 23 114 27 3 709 943 56.434 26 135.163402643019 135.163402643019 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 31 132.9 10/01/06 24 47.9 24 140 28 04/01/03 3 655 530 67.222 27 24 661 26 117.9 24 47.9 24 140 28 3 655 530 67.222 27 140.056298850906 140.056298850906 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 32 124.6 01/01/07 25 25 145 29 05/01/03 4 097 990 70.76 28 27 126.5 25 145 29 4 097 990 70.76 28 139.085125168441 139.085125168441 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 33 118.3 04/01/07 26 26 150 30 06/01/03 4 472 583 73.95 29 28 135.2 1 26 150 30 4 472 583 73.95 29 132.894958841735 132.894958841735 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 34 117.2 07/01/07 27 27 178 31 07/01/03 4 531 711 79.286 30 29 140.1 2 27 178 31 4 531 711 79.286 30 124.587940151099 124.587940151099 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 35 122.1 10/01/07 28 28 163 32 08/01/03 4 504 466 77.372 31 30 139.1 3 28 163 32 4 504 466 77.372 31 118.284971020992 118.284971020992 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 36 131.0 01/01/08 29 29 172 33 09/01/03 4 054 338 79.808 32 31 132.9 4 29 172 33 4 054 338 79.808 32 117.197499210841 117.197499210841 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 37 140.0 04/01/08 30 30 178 34 10/01/03 71.978 33 32 124.6 5 30 178 34 71.978 33 122.111621693591 122.111621693591 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 38 145.0 07/01/08 31 31 199 35 11/01/03 70.702 34 33 118.3 6 31 199 35 70.702 34 131 131 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 39 144.0 10/01/08 32 32 199 36 12/01/03 65.946 35 34 117.2 7 32 199 36 65.946 35 139.952657067378 139.952657067378 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 01/01/09 33 33 184 37 01/01/04 55.274 36 35 122.1 8 33 184 37 55.274 36 144.999462339761 144.999462339761 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 04/01/09 34 34 162 38 02/01/04 61.08 37 36 131.0 34 162 38 61.08 37 143.974836600144 143.974836600144 TRUE {=FORECAST.ETS.MULT(S1:S39,T1:T39,S1:S39)} 35 146 39 02/29/04 59.7 38 37 140.0 35 146 39 59.7 38 #NUM! #NUM! TRUE =FORECAST.ETS.MULT(0,P2:P6,Q2:Q6) 36 166 40 03/31/04 69.48 39 38 145.0 36 166 40 69.48 39 #NUM! #NUM! TRUE =FORECAST.ETS.MULT(-30,P2:P6,Q2:Q6) 37 41 04/30/04 77.34 40 39 144.0 41 77.34 40 5 5.000000 TRUE =FORECAST.ETS.MULT(8, {1,2,3}, {4,5,6}) 38 42 05/31/04 74.16 41 42 74.16 41 #VALUE! #VALUE! TRUE =FORECAST.ETS.MULT(7, {5.8,-1}, {2,-5}) 39 43 06/30/04 83.04 42 43 83.04 42 -5 -5.000000 TRUE =FORECAST.ETS.MULT(50, {-1,-2,-3,-4}, {10,20,30,40}) 40 44 07/31/04 80.16 43 44 80.16 43 47.9 47.900000 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 41 45 08/31/04 81.12 44 45 81.12 44 61.9729295871504 61.972930 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 42 46 09/30/04 84.12 45 46 84.12 45 36.8217963889502 36.821796 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 43 47 10/31/04 69 46 47 69 46 46.4784787396254 46.478479 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 44 48 11/30/04 68.4 47 48 68.4 47 50.5782852506606 50.578285 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 45 49 01/01/05 54.54 48 49 54.54 48 65.1381523477569 65.1381523477569 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 46 50 02/01/05 66.624 49 50 66.624 49 38.6787327078871 38.6787327078871 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 47 51 03/01/05 58.048 50 51 58.048 50 48.7932216644061 48.7932216644061 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 48 52 04/01/05 70.528 51 52 70.528 51 53.0662321817619 53.066232 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 49 53 05/01/05 79.424 52 53 79.424 52 68.3033751083634 68.3033751083634 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} -9.9475983006414E-13 11 50 54 06/01/05 79.232 53 54 79.232 53 40.535669026824 40.535669026824 TRUE {=FORECAST.ETS.MULT(V31:V41,X8:X31,V8:V31,W3,W4,W5)} 51 55 07/01/05 93.056 54 55 93.056 54 166 166 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 52 56 08/01/05 93.76 55 56 93.76 55 173.745949032818 173.745949032818 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 53 57 09/01/05 93.696 56 57 93.696 56 183.787265957111 183.787265957111 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 54 58 10/01/05 94.08 57 58 94.08 57 206.399165266807 206.399165 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 55 59 11/01/05 82.624 58 59 82.624 58 202.483337817381 202.483338 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 56 60 12/01/05 75.776 59 60 75.776 59 190.641123921524 190.641124 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 57 58.048 60 58.048 60 213.483211306267 213.483211 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 58 61 61 234.886744883615 234.886745 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 59 62 62 235.718895043652 235.718895 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 60 63 63 217.358909191697 217.358909 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 61 64 64 190.836835067215 190.836835 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 62 65 65 167.338929526706 167.338930 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 63 66 66 190.487537765425 190.487538 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 67 67 200.127359722618 200.127360 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 68 68 211.344649681028 211.344650 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 69 69 236.965090983393 236.965091 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 70 70 232.103818773717 232.103819 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 71 71 218.193378775663 218.193379 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 72 72 243.969532849646 243.969533 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 73 73 268.03510577085 268.035106 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 74 74 268.59802115122 268.59802115122 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 75 75 247.328741800136 247.328741800136 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 76 76 216.850852063095 216.850852063095 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 77 77 189.893605332791 189.893605332791 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 78 78 215.877108165921 215.877108165921 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 79 79 226.508770412417 226.508770412417 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 80 80 238.902033404945 238.902033404945 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 81 81 267.531016699979 267.531016699979 TRUE {=FORECAST.ETS.MULT(AB43:AB70,AC8:AC43,AB8:AB43,AB3,AB4,AB5)} 82 82 4054338 4054338 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 83 83 4288601.49523545 4288601.49523545 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 84 84 4091199.55229487 4091199.55229487 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 85 85 4038561.97098737 4038561.97098737 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 86 86 3779986.30181304 3779986.30181304 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 87 87 3387827.28877104 3387827.28877104 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 88 88 3815736.59044792 3815736.59044792 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 89 89 3927934.74841799 3927934.74841799 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 90 90 4208549.03819637 4208549.03819637 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 91 91 4719235.05761799 4719235.05761799 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 92 92 4846987.32895276 4846987.32895276 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 93 93 4876844.61506186 4876844.61506186 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 94 94 4465507.06401322 4465507.06401322 TRUE {=FORECAST.ETS.MULT(AE36:AE63,AG4:AG36,AE4:AE36,12,1,1)} 95 95 4527918.73243619 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