Multiple Linear Regression - Estimated Regression Equation
PSS[t] = + 10.2762770653839 -0.115368910871645G[t] -0.0340374480008491T[t] + 0.0258113556187273`T-G`[t] + 1.21566788645044HPP[t] -0.233157283641215`HPP-G`[t] + 1.08065169306244TGYW[t] + 0.0279738297900182`TGYW-G`[t] -0.706210467475044POP[t] + 0.0201781082769354`POP-G`[t] -0.779717192161222IDT[t] + 0.112898678160323`IDT-G `[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)10.27627706538390.56907618.057800
G-0.1153689108716450.014626-7.888200
T-0.03403744800084910.012952-2.62790.0111610.00558
`T-G`0.02581135561872730.0234881.09890.2766820.138341
HPP1.215667886450440.1967426.17900
`HPP-G`-0.2331572836412150.217404-1.07250.2882830.144141
TGYW1.080651693062440.1836675.883700
`TGYW-G`0.02797382979001820.1931940.14480.8854110.442705
POP-0.7062104674750440.198308-3.56120.000780.00039
`POP-G`0.02017810827693540.1935120.10430.9173390.458669
IDT-0.7797171921612220.165482-4.71181.8e-059e-06
`IDT-G `0.1128986781603230.2438580.4630.6452470.322623


Multiple Linear Regression - Regression Statistics
Multiple R0.986956099413074
R-squared0.974082342168669
Adjusted R-squared0.968802819277101
F-TEST (value)184.501963941569
F-TEST (DF numerator)11
F-TEST (DF denominator)54
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.976960556198783
Sum Squared Residuals51.5404041318847


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
11414.1593430366490-0.159343036649043
21818.3435035220867-0.343503522086658
31111.4511820632625-0.451182063262546
41211.92026637871740.07973362128259
51616.2460060994724-0.246006099472436
61818.2073537300833-0.207353730083254
71414.6920035438345-0.69200354383447
81414.7314728205198-0.731472820519804
91515.1027113390928-0.102711339092777
101515.0686738910919-0.0686738910919283
111716.83788941741010.162110582589929
121918.78284623423940.217153765760619
131010.1584747400738-0.158474740073772
141615.71224129124980.287758708750245
151818.275457923663-0.275457923663011
161414.335282559448-0.33528255944799
171413.88524945821430.114750541785694
181716.58323646762260.416763532377376
191413.46541795499290.534582045007084
201615.94396729753390.0560327024661226
211816.99985384393541.00014615606460
221110.87797727593260.122022724067412
231414.0123881824329-0.0123881824328909
241211.89055407299330.109445927006666
251716.59660920401710.403390795982874
2699.12088363090493-0.120883630904928
271615.59764641644370.402353583556342
281413.97721713581660.0227828641833576
291514.7228968799770.277103120022984
301111.0395694627813-0.0395694627813415
311615.43453917613650.56546082386346
321313.2211544785248-0.221154478524815
331716.14618147229610.853818527703936
341514.25177513907150.748224860928451
351414.1789868041877-0.178986804187675
361615.52361158500460.476388414995438
3799.73603701775351-0.73603701775351
381514.39853387738790.601466122612144
391716.37790747858020.622092521419813
401313.1361318942706-0.136131894270632
411514.79644876389580.203551236104156
421615.06012724812720.93987275187280
431615.76250718194080.237492818059175
441212.4364090107412-0.436409010741244
451213.7035673272813-1.70356732728132
4634.71839414864835-1.71839414864835
4744.43275716005653-0.432757160056534
4844.52257170303609-0.522571703036086
4954.330771176407920.66922882359208
5046.15203190796087-2.15203190796087
5134.05404389076897-1.05404389076897
5236.29533950531307-3.29533950531307
5344.12645907299968-0.126459072999678
5433.92177050869039-0.921770508690395
5544.95151233823011-0.951512338230114
5643.394436962211730.605563037788269
5743.276905577168800.723094422831205
5833.24862398883875-0.248623988838746
5933.64719788223852-0.647197882238519
6033.21396560043436-0.213965600434360
6130.3132292053041162.68677079469588
6244.44045804769021-0.440458047690205
6342.982484225958531.01751577404147
6442.671035881747981.32896411825202
6542.461219721014171.53878027898583
6630.9426971655880932.05730283441191


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
153.81580574671502e-447.63161149343004e-441
169.73436777170028e-611.94687355434006e-601
171.74621832128781e-753.49243664257563e-751
183.78698856062550e-877.57397712125101e-871
193.27486288708833e-1016.54972577417665e-1011
201.25475107269315e-1202.50950214538631e-1201
216.18543887774056e-1281.23708777554811e-1271
224.80928537814385e-1459.6185707562877e-1451
232.07391860526198e-1584.14783721052397e-1581
247.28223467152904e-1731.45644693430581e-1721
253.05294000980883e-1916.10588001961766e-1911
261.09440851092711e-2032.18881702185421e-2031
271.19607701610786e-2212.39215403221571e-2211
287.28791881962743e-2271.45758376392549e-2261
292.15995611956016e-2474.31991223912032e-2471
301.42878603150679e-2532.85757206301359e-2531
311.13781453135499e-2742.27562906270999e-2741
329.14324111245473e-2941.82864822249095e-2931
332.63688129818922e-3045.27376259637844e-3041
343.03244647710565e-3186.0648929542113e-3181
35001
36001
37001
38001
39001
40001
41001
42001
43001
44001
4513.87760287613849e-1251.93880143806924e-125
4619.00013478176091e-1184.50006739088046e-118
4714.23144574578171e-962.11572287289085e-96
4812.20110915578591e-871.10055457789295e-87
4912.76733906589568e-711.38366953294784e-71
5011.40597924373098e-587.02989621865492e-59
5114.21748410459427e-452.10874205229713e-45


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level371NOK
5% type I error level371NOK
10% type I error level371NOK