Multiple Linear Regression - Estimated Regression Equation
Yt[t] = + 5.65277449152099e-15 + 0.999999999999998X1t[t] + 1.00000000000000X2t[t] + 1X3t[t] + 1X4t[t] + 1X5t[t] + 1X6t[t] + 1.00000000000000X7t[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)5.65277449152099e-1502.17140.0314740.015737
X1t0.9999999999999980229530461972672200
X2t1.000000000000000173708892548703500
X3t10168083898888042300
X4t10169059727310860700
X5t10197975307053765000
X6t10190717525801107000
X7t1.000000000000000165975030732375200


Multiple Linear Regression - Regression Statistics
Multiple R1
R-squared1
Adjusted R-squared1
F-TEST (value)1.59029440260596e+31
F-TEST (DF numerator)7
F-TEST (DF denominator)150
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation5.02271080728302e-15
Sum Squared Residuals3.78414357803965e-27


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
12423.99999999999995.4679233911816e-14
22525.0000000000000-2.34466723732491e-14
330304.40060569066426e-15
41919-6.162445547409e-15
52222-6.95001114635409e-16
62222-5.18669161073777e-15
725252.07099882053762e-15
823232.12019517737531e-15
917179.6944945555234e-16
1021217.77436210298879e-16
1119194.38141436319459e-16
1219197.12315530563665e-16
131515-3.73653379795946e-16
1416161.34092654939325e-15
152323-2.95342082814583e-16
1627274.63216986012391e-16
1722226.56439306485443e-16
1814145.40082240803923e-16
192222-4.67453343341134e-16
2023232.16539268495076e-16
212323-1.16667692028670e-15
2221213.66942880131265e-16
231919-1.385016727195e-16
241818-3.62226921603343e-16
252020-3.46285400048605e-16
2623231.02214280119796e-15
272525-1.20146484791471e-15
2819198.71717219850532e-17
292424-1.75460259035751e-15
302222-4.31016926757548e-16
312525-1.04784318713914e-15
322626-7.24343648051878e-16
332929-1.35638899308394e-16
343232-2.58269908054916e-16
352525-5.28756467219368e-17
362929-1.76325283274044e-16
3728281.19194075351474e-16
3817171.32978507811277e-15
3928281.19194075351474e-16
4029291.65441480513277e-16
412626-3.12307980184998e-15
422525-2.73792413445623e-17
4314145.40082240803923e-16
442525-2.2599468222865e-16
452626-1.28477335485215e-15
4620206.458702439866e-16
471818-3.11196079984962e-16
483232-1.13498397717451e-15
492525-1.04784318713914e-15
5025258.58523774412738e-16
512323-1.60653517818652e-15
522121-7.129785620458e-16
532020-1.81558244185446e-15
541515-1.2287797014343e-15
5530301.16088935041905e-15
5624247.11106835457189e-16
572626-2.16340039831914e-15
5824242.2839261784989e-17
592222-2.04919174317775e-15
6014143.97073410775532e-16
6124246.46046537787993e-16
6224243.18297824888136e-16
6324242.2839261784989e-17
6424242.19860134884790e-16
6519194.86689791810069e-16
663131-6.27729222140305e-16
672222-3.02797614858376e-16
6827273.81947828900892e-16
691919-6.06449295311223e-16
7025253.96531757615815e-16
7120201.53178949344847e-15
722121-3.43166177506857e-16
7327273.56124243064482e-16
7423231.28192278000074e-15
752525-5.30012838651923e-16
762020-1.81558244185446e-15
772121-3.69604675937102e-16
7822224.38955063764887e-16
7923231.83467728186949e-16
802525-5.28756467219368e-17
812525-6.36044127085785e-16
8217171.32978507811277e-15
8319192.37877032938004e-15
842525-2.12177931580617e-16
8519194.38141436319459e-16
8620208.67345083381545e-16
8726262.37550122262004e-16
882323-1.61578293218882e-15
8927273.56124243064482e-16
901717-2.97452024302629e-16
9117171.07515356352717e-15
921919-1.06275845822984e-15
931717-6.36140748408697e-16
942222-4.67453343341134e-16
952121-1.88098814184504e-15
963232-1.25099729366568e-15
972121-3.69604675937102e-16
9821219.52989789784179e-16
991818-6.89940385366812e-16
1001818-1.56503167576656e-16
10123238.71717219850532e-17
1021919-6.03477925834168e-17
1032020-3.43166177506857e-16
1042121-2.7137233371064e-16
10520203.8740123706713e-16
10617177.81102892466329e-16
1071818-1.26529090409144e-15
1081919-2.01221420158322e-15
1092222-1.85204654553362e-16
1101515-8.58368178089289e-16
1111414-8.85982709039911e-16
1121818-4.17320388550468e-16
1132424-9.23917275843618e-16
11435357.46141745770695e-17
1152929-1.09847858098335e-15
1162121-2.3705594404562e-15
1172525-1.48475568927335e-15
11820201.39860867927233e-15
11922221.35597572495392e-15
12013131.61876993845633e-16
1212626-5.5871432562863e-16
12217171.07722196656207e-15
12325252.49679571505464e-16
12420201.87412014690547e-15
12519198.10163784511347e-16
1262121-9.31659726921099e-16
1272222-4.61856279439127e-16
1282424-1.19432992028941e-15
1292121-1.28477335485215e-15
1302626-1.36401985913911e-16
1312424-1.70001156246394e-15
1321616-7.13551212464841e-16
1332323-1.27755875474837e-15
13418182.85632355932166e-16
1351616-1.28477335485215e-15
13626261.97255783690882e-15
13719198.14333699301813e-16
1382121-7.16017700782112e-16
13921218.88336680079244e-16
14022221.6803345918565e-15
1412323-2.67185608551446e-16
1422929-3.33351947284590e-16
1432121-1.72572187981651e-15
1442121-1.14348170687555e-15
14523232.58013733520171e-16
1462727-6.81721525080088e-16
1472525-5.30455275752571e-16
1482121-7.36848301521211e-16
1491010-6.14042652104326e-16
15020201.22726050535130e-15
1512626-2.1283110782555e-15
1522424-1.33027470068247e-15
15329293.40334549005982e-16
15419192.18554800890698e-15
1552424-1.17441156338223e-15
1561919-1.05042300688226e-15
15724247.70453382242686e-17
15822224.12462447823937e-16
15917NANA


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.1987272938695510.3974545877391020.80127270613045
120.0004904914751119960.0009809829502239910.999509508524888
131.94688890818687e-063.89377781637374e-060.999998053111092
140.05768266275885370.1153653255177070.942317337241146
150.0001329720446986310.0002659440893972620.999867027955301
162.70906270740679e-085.41812541481358e-080.999999972909373
177.82291503356155e-131.56458300671231e-120.999999999999218
185.43588848424815e-111.08717769684963e-100.99999999994564
194.86549774806163e-089.73099549612327e-080.999999951345023
202.26872957874386e-114.53745915748772e-110.999999999977313
211.21659006195967e-072.43318012391935e-070.999999878340994
224.71127242425764e-099.42254484851528e-090.999999995288728
230.921418889391870.1571622212162600.0785811106081302
248.15931656494636e-061.63186331298927e-050.999991840683435
252.33936528157533e-074.67873056315065e-070.999999766063472
260.0001306949769049840.0002613899538099670.999869305023095
270.6877790478898010.6244419042203980.312220952110199
284.7555550200333e-179.5111100400666e-171
290.9969439099813710.006112180037257170.00305609001862858
301.18640835779094e-062.37281671558188e-060.999998813591642
310.00237979369601840.00475958739203680.997620206303982
3212.17032219948718e-361.08516109974359e-36
331.21346827995270e-052.42693655990539e-050.9999878653172
340.007225371888355830.01445074377671170.992774628111644
350.00102543750612230.00205087501224460.998974562493878
363.47798144082734e-246.95596288165467e-241
373.56528677374145e-157.1305735474829e-150.999999999999996
383.48854217370139e-216.97708434740277e-211
397.6418565557708e-201.52837131115416e-191
400.9958179635973230.008364072805353620.00418203640267681
410.1267715232698210.2535430465396430.873228476730179
420.8615209412810040.2769581174379910.138479058718996
431.52260053609570e-063.04520107219141e-060.999998477399464
440.4882630592510340.9765261185020680.511736940748966
456.05105651649973e-151.21021130329995e-140.999999999999994
460.001442731430769620.002885462861539250.99855726856923
475.910425385906e-171.1820850771812e-161
484.26411668105976e-238.52823336211952e-231
491.95143593707703e-213.90287187415406e-211
500.939778429869390.1204431402612190.0602215701306094
510.9994307943487920.001138411302416210.000569205651208105
520.01121496237935940.02242992475871890.98878503762064
532.03010174963882e-064.06020349927764e-060.99999796989825
542.05309699349572e-464.10619398699143e-461
5517.14505104207465e-173.57252552103733e-17
560.03094158357245050.06188316714490090.96905841642755
5711.00327916640463e-325.01639583202317e-33
585.45616859408648e-211.09123371881730e-201
590.9999263071983450.0001473856033101797.36928016550894e-05
600.7782531458391550.443493708321690.221746854160845
6116.57638899936315e-333.28819449968158e-33
621.73056098794098e-063.46112197588196e-060.999998269439012
632.48310030101095e-364.9662006020219e-361
642.15316826675274e-174.30633653350548e-171
650.9137406115740310.1725187768519380.0862593884259692
6611.19301945875477e-365.96509729377384e-37
670.9978002077108830.004399584578234120.00219979228911706
6812.65526352413373e-381.32763176206687e-38
691.59887962088185e-193.1977592417637e-191
700.2965202508520070.5930405017040130.703479749147993
710.1466240268863720.2932480537727440.853375973113628
7211.17993338638020e-695.89966693190098e-70
734.72341726308488e-459.44683452616976e-451
744.01124780059783e-138.02249560119567e-130.9999999999996
752.73421917446137e-235.46843834892273e-231
763.0629804335193e-156.1259608670386e-150.999999999999997
771.05803165581653e-442.11606331163306e-441
780.9999999999992361.52730932080693e-127.63654660403465e-13
791.49191426289055e-372.98382852578111e-371
803.90789497978888e-077.81578995957775e-070.999999609210502
8111.99430642065003e-959.97153210325013e-96
820.9999999899175562.01648890094061e-081.00824445047030e-08
831.40309893562625e-332.80619787125249e-331
8412.96674520049018e-161.48337260024509e-16
850.9999999985968662.80626892269445e-091.40313446134722e-09
860.9998946434189620.0002107131620764710.000105356581038236
8715.46741031049254e-292.73370515524627e-29
883.15633442070998e-056.31266884141996e-050.999968436655793
890.01569737042228200.03139474084456400.984302629577718
903.37200759402839e-086.74401518805677e-080.999999966279924
9116.01706842051864e-253.00853421025932e-25
920.9994481054152940.001103789169412530.000551894584706264
930.9999999999770554.58900846909031e-112.29450423454516e-11
940.999999999871452.57098416524765e-101.28549208262382e-10
950.9999974815841175.03683176636401e-062.51841588318200e-06
960.9999999999896582.06845786084223e-111.03422893042111e-11
970.000972018026174770.001944036052349540.999027981973825
9817.49059524779674e-383.74529762389837e-38
992.53653331870966e-075.07306663741932e-070.999999746346668
10018.49598251502897e-564.24799125751449e-56
1010.9999999852902392.941952254783e-081.4709761273915e-08
10219.7653925436888e-184.8826962718444e-18
1031.37044041150991e-172.74088082301982e-171
10417.1771670206962e-453.5885835103481e-45
10511.31631077905512e-156.58155389527561e-16
1061.08318025860870e-162.16636051721740e-161
1070.9974582722385970.005083455522806530.00254172776140327
1080.000793517663755890.001587035327511780.999206482336244
10918.95310763600885e-184.47655381800442e-18
1105.3106178648092e-301.06212357296184e-291
11111.28390320646231e-186.41951603231153e-19
11211.10400558791487e-185.52002793957433e-19
11316.21493048831439e-173.10746524415720e-17
1141.72747190175854e-183.45494380351709e-181
1155.42040149392627e-411.08408029878525e-401
1160.9489738075996950.1020523848006090.0510261924003046
1170.002823153107695630.005646306215391250.997176846892304
1180.1283674959503300.2567349919006600.87163250404967
1190.9999999999093061.81387424317920e-109.06937121589602e-11
1200.6160049026197150.767990194760570.383995097380285
12113.81318743666095e-291.90659371833048e-29
12213.27713339019568e-271.63856669509784e-27
1230.9999102436018120.0001795127963761298.97563981880647e-05
1240.999855915760060.0002881684798776990.000144084239938849
1250.9999983336929693.33261406264709e-061.66630703132354e-06
12614.92231723801526e-292.46115861900763e-29
1270.999999999991131.77414281440152e-118.87071407200762e-12
12811.0641748143815e-235.3208740719075e-24
1290.9933193383738640.01336132325227210.00668066162613604
1300.9999998473256283.05348744952807e-071.52674372476404e-07
1311.78194535966749e-053.56389071933499e-050.999982180546403
1320.7654052817593430.4691894364813150.234594718240657
1330.9999999998656712.68658115532553e-101.34329057766277e-10
13417.30904477198118e-163.65452238599059e-16
1350.9999999316168541.36766292885816e-076.8383146442908e-08
1360.999999871224092.57551820504207e-071.28775910252103e-07
1370.9999997624581794.75083642392734e-072.37541821196367e-07
13811.68954833573697e-188.44774167868483e-19
1390.9999999999999823.64195639708312e-141.82097819854156e-14
1400.9999999612541387.74917233687675e-083.87458616843838e-08
1410.9999999972574555.48508918887605e-092.74254459443803e-09
1420.99999999715935.68139785080545e-092.84069892540273e-09
1430.9999999998872722.25456084643568e-101.12728042321784e-10
1440.8666270651862770.2667458696274450.133372934813723
1450.9996205451412250.000758909717549790.000379454858774895
1460.9999999366966891.26606622515509e-076.33033112577543e-08
1470.9967429318653870.006514136269225470.00325706813461274
1480.3827861926827660.7655723853655330.617213807317234


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1150.833333333333333NOK
5% type I error level1190.86231884057971NOK
10% type I error level1200.869565217391304NOK