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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 07 Dec 2012 10:18:32 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/07/t1354893556yaskbg1wzdle80p.htm/, Retrieved Tue, 23 Apr 2024 07:54:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197421, Retrieved Tue, 23 Apr 2024 07:54:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2012-11-19 08:53:41] [d1865ed705b6ad9ba3d459a02c528b22]
- R  D    [Multiple Regression] [Paper_D3_Multiple...] [2012-12-07 15:18:32] [ddb0733c84f7879813cb9fbdaebb43ad] [Current]
- RMPD      [Notched Boxplots] [Paper2012: Notche...] [2012-12-19 12:35:27] [f055db2f1c47e4197bf514e64f7886e5]
- RMPD      [Histogram] [Paper2012: Histogram] [2012-12-19 12:42:06] [f055db2f1c47e4197bf514e64f7886e5]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
210907	56	3	79	30	112285
120982	56	4	58	28	84786
176508	54	12	60	38	83123
179321	89	2	108	30	101193
123185	40	1	49	22	38361
52746	25	3	0	26	68504
385534	92	0	121	25	119182
33170	18	0	1	18	22807
101645	63	0	20	11	17140
149061	44	5	43	26	116174
165446	33	0	69	25	57635
237213	84	0	78	38	66198
173326	88	7	86	44	71701
133131	55	7	44	30	57793
258873	60	3	104	40	80444
180083	66	9	63	34	53855
324799	154	0	158	47	97668
230964	53	4	102	30	133824
236785	119	3	77	31	101481
135473	41	0	82	23	99645
202925	61	7	115	36	114789
215147	58	0	101	36	99052
344297	75	1	80	30	67654
153935	33	5	50	25	65553
132943	40	7	83	39	97500
174724	92	0	123	34	69112
174415	100	0	73	31	82753
225548	112	5	81	31	85323
223632	73	0	105	33	72654
124817	40	0	47	25	30727
221698	45	0	105	33	77873
210767	60	3	94	35	117478
170266	62	4	44	42	74007
260561	75	1	114	43	90183
84853	31	4	38	30	61542
294424	77	2	107	33	101494
101011	34	0	30	13	27570
215641	46	0	71	32	55813
325107	99	0	84	36	79215
7176	17	0	0	0	1423
167542	66	2	59	28	55461
106408	30	1	33	14	31081
96560	76	0	42	17	22996
265769	146	2	96	32	83122
269651	67	10	106	30	70106
149112	56	6	56	35	60578
175824	107	0	57	20	39992
152871	58	5	59	28	79892
111665	34	4	39	28	49810
116408	61	1	34	39	71570
362301	119	2	76	34	100708
78800	42	2	20	26	33032
183167	66	0	91	39	82875
277965	89	8	115	39	139077
150629	44	3	85	33	71595
168809	66	0	76	28	72260
24188	24	0	8	4	5950
329267	259	8	79	39	115762
65029	17	5	21	18	32551
101097	64	3	30	14	31701
218946	41	1	76	29	80670
244052	68	5	101	44	143558
341570	168	1	94	21	117105
103597	43	1	27	16	23789
233328	132	5	92	28	120733
256462	105	0	123	35	105195
206161	71	12	75	28	73107
311473	112	8	128	38	132068
235800	94	8	105	23	149193
177939	82	8	55	36	46821
207176	70	8	56	32	87011
196553	57	2	41	29	95260
174184	53	0	72	25	55183
143246	103	5	67	27	106671
187559	121	8	75	36	73511
187681	62	2	114	28	92945
119016	52	5	118	23	78664
182192	52	12	77	40	70054
73566	32	6	22	23	22618
194979	62	7	66	40	74011
167488	45	2	69	28	83737
143756	46	0	105	34	69094
275541	63	4	116	33	93133
243199	75	3	88	28	95536
182999	88	6	73	34	225920
135649	46	2	99	30	62133
152299	53	0	62	33	61370
120221	37	1	53	22	43836
346485	90	0	118	38	106117
145790	63	5	30	26	38692
193339	78	2	100	35	84651
80953	25	0	49	8	56622
122774	45	0	24	24	15986
130585	46	5	67	29	95364
112611	41	0	46	20	26706
286468	144	1	57	29	89691
241066	82	0	75	45	67267
148446	91	1	135	37	126846
204713	71	1	68	33	41140
182079	63	2	124	33	102860
140344	53	6	33	25	51715
220516	62	1	98	32	55801
243060	63	4	58	29	111813
162765	32	2	68	28	120293
182613	39	3	81	28	138599
232138	62	0	131	31	161647
265318	117	10	110	52	115929
85574	34	0	37	21	24266
310839	92	9	130	24	162901
225060	93	7	93	41	109825
232317	54	0	118	33	129838
144966	144	0	39	32	37510
43287	14	4	13	19	43750
155754	61	4	74	20	40652
164709	109	0	81	31	87771
201940	38	0	109	31	85872
235454	73	0	151	32	89275
220801	75	1	51	18	44418
99466	50	0	28	23	192565
92661	61	1	40	17	35232
133328	55	0	56	20	40909
61361	77	0	27	12	13294
125930	75	4	37	17	32387
100750	72	0	83	30	140867
224549	50	4	54	31	120662
82316	32	4	27	10	21233
102010	53	3	28	13	44332
101523	42	0	59	22	61056
243511	71	0	133	42	101338
22938	10	0	12	1	1168
41566	35	5	0	9	13497
152474	65	0	106	32	65567
61857	25	4	23	11	25162
99923	66	0	44	25	32334
132487	41	0	71	36	40735
317394	86	1	116	31	91413
21054	16	0	4	0	855
209641	42	5	62	24	97068
22648	19	0	12	13	44339
31414	19	0	18	8	14116
46698	45	0	14	13	10288
131698	65	0	60	19	65622
91735	35	0	7	18	16563
244749	95	2	98	33	76643
184510	49	7	64	40	110681
79863	37	1	29	22	29011
128423	64	8	32	38	92696
97839	38	2	25	24	94785
38214	34	0	16	8	8773
151101	32	2	48	35	83209
272458	65	0	100	43	93815
172494	52	0	46	43	86687
108043	62	1	45	14	34553
328107	65	3	129	41	105547
250579	83	0	130	38	103487
351067	95	3	136	45	213688
158015	29	0	59	31	71220
98866	18	0	25	13	23517
85439	33	0	32	28	56926
229242	247	4	63	31	91721
351619	139	4	95	40	115168
84207	29	11	14	30	111194
120445	118	0	36	16	51009
324598	110	0	113	37	135777
131069	67	4	47	30	51513
204271	42	0	92	35	74163
165543	65	1	70	32	51633
141722	94	0	19	27	75345
116048	64	0	50	20	33416
250047	81	0	41	18	83305
299775	95	9	91	31	98952
195838	67	1	111	31	102372
173260	63	3	41	21	37238
254488	83	10	120	39	103772
104389	45	5	135	41	123969
136084	30	0	27	13	27142
199476	70	2	87	32	135400
92499	32	0	25	18	21399
224330	83	1	131	39	130115
135781	31	2	45	14	24874
74408	67	4	29	7	34988
81240	66	0	58	17	45549
14688	10	0	4	0	6023
181633	70	2	47	30	64466
271856	103	1	109	37	54990
7199	5	0	7	0	1644
46660	20	0	12	5	6179
17547	5	0	0	1	3926
133368	36	1	37	16	32755
95227	34	0	37	32	34777
152601	48	2	46	24	73224
98146	40	0	15	17	27114
79619	43	3	42	11	20760
59194	31	6	7	24	37636
139942	42	0	54	22	65461
118612	46	2	54	12	30080
72880	33	0	14	19	24094
65475	18	2	16	13	69008
99643	55	1	33	17	54968
71965	35	1	32	15	46090
77272	59	2	21	16	27507
49289	19	1	15	24	10672
135131	66	0	38	15	34029
108446	60	1	22	17	46300
89746	36	3	28	18	24760
44296	25	0	10	20	18779
77648	47	0	31	16	21280
181528	54	0	32	16	40662
134019	53	0	32	18	28987
124064	40	1	43	22	22827
92630	40	4	27	8	18513
121848	39	0	37	17	30594
52915	14	0	20	18	24006
81872	45	0	32	16	27913
58981	36	7	0	23	42744
53515	28	2	5	22	12934
60812	44	0	26	13	22574
56375	30	7	10	13	41385
65490	22	3	27	16	18653
80949	17	0	11	16	18472
76302	31	0	29	20	30976
104011	55	6	25	22	63339
98104	54	2	55	17	25568
67989	21	0	23	18	33747
30989	14	0	5	17	4154
135458	81	3	43	12	19474
73504	35	0	23	7	35130
63123	43	1	34	17	39067
61254	46	1	36	14	13310
74914	30	0	35	23	65892
31774	23	1	0	17	4143
81437	38	0	37	14	28579
87186	54	0	28	15	51776
50090	20	0	16	17	21152
65745	53	0	26	21	38084
56653	45	0	38	18	27717
158399	39	0	23	18	32928
46455	20	0	22	17	11342
73624	24	0	30	17	19499
38395	31	0	16	16	16380
91899	35	0	18	15	36874
139526	151	0	28	21	48259
52164	52	0	32	16	16734
51567	30	2	21	14	28207
70551	31	0	23	15	30143
84856	29	1	29	17	41369
102538	57	1	50	15	45833
86678	40	0	12	15	29156
85709	44	0	21	10	35944
34662	25	0	18	6	36278
150580	77	0	27	22	45588
99611	35	0	41	21	45097
19349	11	0	13	1	3895
99373	63	1	12	18	28394
86230	44	0	21	17	18632
30837	19	0	8	4	2325
31706	13	0	26	10	25139
89806	42	0	27	16	27975
62088	38	1	13	16	14483
40151	29	0	16	9	13127
27634	20	0	2	16	5839
76990	27	0	42	17	24069
37460	20	0	5	7	3738
54157	19	0	37	15	18625
49862	37	0	17	14	36341
84337	26	0	38	14	24548
64175	42	0	37	18	21792
59382	49	0	29	12	26263
119308	30	0	32	16	23686
76702	49	0	35	21	49303
103425	67	1	17	19	25659
70344	28	0	20	16	28904
43410	19	0	7	1	2781
104838	49	1	46	16	29236
62215	27	0	24	10	19546
69304	30	6	40	19	22818
53117	22	3	3	12	32689
19764	12	1	10	2	5752
86680	31	2	37	14	22197
84105	20	0	17	17	20055
77945	20	0	28	19	25272
89113	39	0	19	14	82206
91005	29	3	29	11	32073
40248	16	1	8	4	5444
64187	27	0	10	16	20154
50857	21	0	15	20	36944
56613	19	1	15	12	8019
62792	35	0	28	15	30884
72535	14	0	17	16	19540

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net
R Engine error message
Error in array(list(210907, 56, 3, 79, 30, 112285, 120982, 56, 4, 58,  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted


\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
R Engine error message & 
Error in array(list(210907, 56, 3, 79, 30, 112285, 120982, 56, 4, 58,  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted

 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197421&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[ROW][C]R Engine error message[/C][C]
Error in array(list(210907, 56, 3, 79, 30, 112285, 120982, 56, 4, 58,  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted

[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197421&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197421&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net
R Engine error message
Error in array(list(210907, 56, 3, 79, 30, 112285, 120982, 56, 4, 58,  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}