Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 7058102.37766021 -2793503.20246403X[t] + 0.360299173377357Y1[t] + 0.152048144010289Y2[t] + 0.3745587444819Y3[t] -0.320617214160464Y4[t] -1277764.43976877M1[t] -301214.211190674M2[t] -613984.12257938M3[t] + 1702120.12956651M4[t] -697110.854102996M5[t] -310757.834273430M6[t] + 31032.2778017763M7[t] -794467.94169392M8[t] -1913826.67528654M9[t] + 447318.9919382M10[t] + 1871094.16661258M11[t] + 62686.6577060315t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)7058102.377660211705473.862394.13850.0001879.3e-05
X-2793503.20246403626762.642767-4.4577.1e-053.6e-05
Y10.3602991733773570.1263692.85120.0070040.003502
Y20.1520481440102890.1225651.24050.2223790.111189
Y30.37455874448190.1200633.11970.0034480.001724
Y4-0.3206172141604640.110861-2.89210.00630.00315
M1-1277764.43976877647489.781113-1.97340.0557530.027877
M2-301214.211190674675546.515769-0.44590.6582130.329106
M3-613984.12257938674823.388649-0.90980.368640.18432
M41702120.12956651668428.1725442.54650.0150570.007528
M5-697110.854102996621690.910914-1.12130.269190.134595
M6-310757.834273430612045.124272-0.50770.6145730.307286
M731032.2778017763721473.9427650.0430.9659170.482958
M8-794467.94169392637796.661994-1.24560.2205210.11026
M9-1913826.67528654693698.412609-2.75890.0088720.004436
M10447318.9919382820443.4852880.54520.5887910.294395
M111871094.16661258683553.7380462.73730.0093710.004685
t62686.657706031516390.4078873.82460.0004730.000237


Multiple Linear Regression - Regression Statistics
Multiple R0.936477260038661
R-squared0.876989658569518
Adjusted R-squared0.821958716350618
F-TEST (value)15.9363009828373
F-TEST (DF numerator)17
F-TEST (DF denominator)38
p-value2.46369591394568e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation822642.663004327
Sum Squared Residuals25716156137804.4


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
117972385.8315957316.04053122015069.78946881
216896235.5516456891.4315774439344.118422616
316697955.9417180920.9340329-482964.994032918
419691579.5218673134.37503471018445.14496525
515930700.7516874554.3425273-943853.592527275
617444615.9816694492.3602775750123.619722504
717699369.8818257456.6449242-558086.764924161
815189796.8115448141.4209251-258344.610925058
915672722.7515298859.7618952373862.988104766
1017180794.317125146.993677055647.3063230449
1117664893.4518206732.7277884-541839.277788402
1217862884.9817787541.682871475343.2971285835
1316162288.8817127433.4795061-965144.599506103
1417463628.8217281861.1120908181767.707909166
1516772112.1717161026.0204014-388913.850401367
1619106861.4818788077.7426223318783.737377711
1716721314.2518220266.4779752-1498952.22797515
1818161267.8517488544.1653530672723.684646968
1918509941.219145329.9102478-635388.710247796
2017802737.9717084996.9456764717741.02432356
2116409869.7517130729.9860034-720860.236003403
2217967742.0418614108.8445430-646366.804542972
2320286602.2720073407.9154846213194.354515382
2419537280.8119042385.9786602494894.831339799
2518021889.6218939998.9055509-918109.285550902
2620194317.2319688377.3642148505939.865785151
2719049596.6218966474.152507283122.4674927592
2820244720.9420935779.0964159-691058.156415871
2921473302.2420155346.69065131317955.54934873
3019673603.1920103476.8269737-429873.636973670
3121053177.2920860988.4209119192188.869088106
3220159479.8420398591.8058036-239111.965803580
3318203628.3118161685.628473341942.6815267043
3421289464.9420838687.2638710450777.676129021
3520432335.7119569029.2861691863306.423830858
3617180395.0717474948.049778-294552.979777997
3715816786.3216740780.5973217-923994.277321695
3815071819.7515483841.2475146-412021.497514609
3914521120.6113814780.5575235706340.05247648
4015668789.3916413760.8053831-744971.415383076
4114346884.1114565150.5055092-218266.395509183
4213881008.1314744989.6391656-863981.509165582
4315465943.6915387051.435500378892.2544997095
4414238232.9214261359.7187137-23126.7987136971
4513557713.2113252658.6436281305054.566371932
4616127590.2915987648.4679091139941.822090906
4716793894.217328555.7005578-534661.50055784
4816014007.4316289692.5786904-275685.148690384
4916867867.1516075688.7770901792178.372909895
5016014583.2116729613.4046023-715030.194602325
5115878594.8515796178.525535082416.324465046
5218664899.1418566098.45054498800.6894559813
5317962530.0616619413.39333711343116.66666288
5417332692.217461684.3582302-128992.158230219
5519542066.3518619671.9984159922394.351584143
5617203555.1917400712.8388812-197157.648881226


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
210.829973497036110.3400530059277820.170026502963891
220.833147925842590.3337041483148210.166852074157411
230.7876215527448030.4247568945103940.212378447255197
240.7574486835213640.4851026329572720.242551316478636
250.6634802498940470.6730395002119060.336519750105953
260.6663547371862910.6672905256274170.333645262813709
270.6328070947761760.7343858104476480.367192905223824
280.5119440589553260.9761118820893480.488055941044674
290.8798020870107730.2403958259784540.120197912989227
300.8980771440222060.2038457119555890.101922855977794
310.8915004140353210.2169991719293570.108499585964679
320.8189366604111130.3621266791777750.181063339588887
330.8121994036846840.3756011926306320.187800596315316
340.6858475044043180.6283049911913650.314152495595682
350.6108650264556250.778269947088750.389134973544375


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level00OK