Multiple Linear Regression - Estimated Regression Equation
Garnalen[t] = + 1054.73859795288 -0.389954780048043Kabeljauw[t] -0.116309920068412Tong[t] + 0.244707593115734Zeeduivel[t] + 58.4447910371906Olie[t] -15.5934957349337t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)1054.738597952881242.5747090.84880.3991880.199594
Kabeljauw-0.3899547800480430.313731-1.2430.2184890.109245
Tong-0.1163099200684120.07456-1.560.1237790.06189
Zeeduivel0.2447075931157340.0976372.50630.0147950.007397
Olie58.44479103719068.1106397.205900
t-15.59349573493377.10635-2.19430.0319090.015954


Multiple Linear Regression - Regression Statistics
Multiple R0.703122021824278
R-squared0.494380577574261
Adjusted R-squared0.454252051984917
F-TEST (value)12.3199287866569
F-TEST (DF numerator)5
F-TEST (DF denominator)63
p-value2.40444402166418e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1090.81058453612
Sum Squared Residuals74961667.0741697


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
130102467.52656103045542.473438969554
229102732.74315101361177.256848986392
338403021.08491236269818.915087637313
435802880.79295954853699.207040451474
531402658.1337153329481.8662846671
635502837.40224242717712.597757572826
732502773.5662674494476.433732550602
828203301.9792445733-481.979244573303
922603282.63802063055-1022.63802063055
1020603103.88197416382-1043.88197416382
1121203005.70838793527-885.708387935272
1222103230.22203051119-1020.22203051119
1321903289.29263366026-1099.29263366026
1421803240.87541810091-1060.87541810091
1523502845.92458443243-495.924584432433
1624403163.62007876489-723.620078764891
1723703314.08168053366-944.081680533656
1824402997.31487474157-557.314874741566
1926103348.71140839267-738.711408392674
2030403358.31837301715-318.318373017154
2131902560.17554614288629.824453857116
2231202315.71862661202804.281373387976
2331703402.07974367798-232.079743677979
2436003991.7910675511-391.791067551099
2534202383.481260614421036.51873938558
2636502909.43487949841740.565120501589
2741802997.645669557591182.35433044241
2829603035.62221856718-75.6222185671848
2927102927.60518778269-217.605187782690
3029503234.76339323665-284.763393236652
3130303351.58530829495-321.585308294952
3237703317.83026889757452.169731102431
3347403615.682627505931124.31737249407
3444504070.73120616998379.268793830018
3555505053.35261572309496.647384276913
3655805232.18350117907347.816498820933
3758904775.240756688621114.75924331138
3874805171.91363447562308.08636552440
39104505381.847729134975068.15227086503
4063605735.12277705153624.877222948473
4167106091.69750834594618.302491654064
4262006502.39279965423-302.392799654229
4344906215.78202853109-1725.78202853109
4434805439.15787542671-1959.15787542671
4525204431.2870302797-1911.28703027970
4619203359.09295347234-1439.09295347234
4720102311.36989226247-301.369892262471
4819502062.29996250834-112.299962508339
4922403549.44389266759-1309.44389266759
5023701967.56075122512402.439248774879
5128402099.38449283507740.61550716493
5227002548.68506685741151.314933142592
5329802404.81498668755575.185013312445
5432902740.45480732615549.545192673847
5533002380.85120456913919.148795430874
5630002747.00811955736252.991880442644
5723302545.66452811223-215.664528112230
5821903141.39934739862-951.399347398616
5919703284.82409133136-1314.82409133136
6021703011.76782380086-841.767823800859
6128303635.58902190936-805.589021909361
6231903606.91716935954-416.917169359536
6335503852.27577345224-302.275773452241
6432404008.75512930663-768.755129306631
6534503313.1163402074136.8836597926
6635702443.128626542371126.87137345763
6732302375.58839863059854.411601369415
6832602914.5347881434345.4652118566
6927002997.52905261454-297.529052614543


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.03314869768789870.06629739537579740.966851302312101
100.02477425963254280.04954851926508560.975225740367457
110.01873357269925380.03746714539850760.981266427300746
120.01252436954984340.02504873909968680.987475630450157
130.004666444120990720.009332888241981450.99533355587901
140.002585220238962370.005170440477924750.997414779761038
150.001374055953522340.002748111907044680.998625944046478
160.0004812780500254660.0009625561000509320.999518721949975
170.0002392547899257610.0004785095798515230.999760745210074
180.0001198284434626650.000239656886925330.999880171556537
198.1652100180557e-050.0001633042003611140.99991834789982
208.21371466234157e-050.0001642742932468310.999917862853377
214.49547343776795e-058.99094687553591e-050.999955045265622
221.60678323657249e-053.21356647314498e-050.999983932167634
231.24946547448530e-052.49893094897060e-050.999987505345255
246.00202270161522e-061.20040454032304e-050.999993997977298
252.26591177520537e-064.53182355041074e-060.999997734088225
263.31641318283158e-066.63282636566316e-060.999996683586817
272.09230401870338e-054.18460803740677e-050.999979076959813
288.6381985881277e-061.72763971762554e-050.999991361801412
295.37581103993991e-061.07516220798798e-050.99999462418896
308.340662792114e-061.6681325584228e-050.999991659337208
315.4709959470224e-061.09419918940448e-050.999994529004053
322.61306197772195e-065.2261239554439e-060.999997386938022
337.91349219094824e-061.58269843818965e-050.99999208650781
341.18568518216917e-052.37137036433834e-050.999988143148178
359.35449039048027e-050.0001870898078096050.999906455096095
368.3988848563861e-050.0001679776971277220.999916011151436
370.0001956964055313410.0003913928110626820.999804303594469
380.004553591481720160.009107182963440310.99544640851828
390.9685187184149290.06296256317014190.0314812815850709
400.9771529448452960.04569411030940840.0228470551547042
410.9938726434281170.01225471314376700.00612735657188348
420.9996206390239210.0007587219521573660.000379360976078683
430.9999099236562880.0001801526874248749.00763437124369e-05
440.9999772459958354.55080083302163e-052.27540041651081e-05
450.9999785429374384.29141251237662e-052.14570625618831e-05
460.9999649526689197.00946621625266e-053.50473310812633e-05
470.9999151281591470.0001697436817051128.4871840852556e-05
480.999796241367740.0004075172645183080.000203758632259154
490.9998125022338180.0003749955323634680.000187497766181734
500.9995644418723080.0008711162553845620.000435558127692281
510.9989403301099470.002119339780106350.00105966989005318
520.9980636581434770.003872683713045860.00193634185652293
530.9960380320936530.007923935812694290.00396196790634714
540.9929321673589120.01413566528217530.00706783264108767
550.9857543998581030.02849120028379420.0142456001418971
560.9886454218201780.02270915635964340.0113545781798217
570.9741006063283880.05179878734322410.0258993936716120
580.9406518198907110.1186963602185780.0593481801092891
590.9067891347147720.1864217305704570.0932108652852283
600.9432040288443310.1135919423113380.0567959711556689


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level380.730769230769231NOK
5% type I error level460.884615384615385NOK
10% type I error level490.942307692307692NOK