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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSat, 03 Nov 2012 06:18:20 -0400
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/Nov/03/t1351938027nhhltnu4wxh5go1.htm/, Retrieved Fri, 07 Oct 2022 00:36:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185704, Retrieved Fri, 07 Oct 2022 00:36:24 +0000
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Original text written by user:
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User-defined keywordserrror
Estimated Impact87
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [Multiple Regression?] [2012-11-03 10:18:20] [b4b733de199089e913cc2b6ea19b06b9] [Current]
- R  D      [Multiple Regression] [Multiple Regressi...] [2012-11-03 10:29:14] [2c4ddb4bf62114b8025bb962e2c7a2b5]
-             [Multiple Regression] [Multiple Regressi...] [2012-11-03 14:54:43] [2c4ddb4bf62114b8025bb962e2c7a2b5]
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Dataseries X:
-3	5	17	10	-1	9	-15	-1	23	6	NA	24
-2	5	22	16	-4	8	-14	1	23	6	NA	29
0	9	29	21	-6	6	-14	1	23	8	NA	29
1	10	26	13	-9	3	-16	-4	19	4	NA	25
11	14	29	12	-13	21	-24	0	26	8	NA	16
14	19	42	15	-13	22	-19	-2	24	10	NA	18
14	18	40	17	-10	9	-15	-5	23	9	NA	13
16	16	34	17	-12	19	-15	2	27	12	NA	22
14	8	46	21	-9	14	-14	0	24	9	NA	15
10	10	43	18	-15	14	-13	0	24	11	NA	20
15	12	44	15	-14	23	-11	4	26	11	NA	19
18	13	40	15	-18	23	-12	2	24	11	NA	18
18	15	41	21	-13	27	-10	3	25	11	NA	13
12	3	42	24	-2	25	-21	2	27	11	NA	17
8	2	35	29	-1	20	-16	2	25	9	NA	17
2	-2	40	33	5	19	-14	1	23	8	NA	13
-2	1	43	36	8	19	-11	0	24	6	NA	14
-1	1	47	31	6	17	-14	0	24	7	NA	13
1	-1	41	38	7	12	-12	1	26	8	NA	17
-6	-6	44	44	15	13	-14	0	25	6	NA	17
-16	-13	38	44	23	13	-12	0	24	5	NA	15
-21	-25	35	42	43	11	-18	-3	24	2	NA	9
-38	-26	34	32	60	4	-15	-5	22	3	NA	10
-32	-9	31	32	36	8	-13	-6	22	3	NA	9
-22	1	25	18	28	1	-12	-2	22	7	NA	14
-31	3	35	5	23	5	-12	-1	27	8	NA	18
-22	6	36	2	23	4	-16	-3	24	7	NA	18
-26	2	41	9	22	3	-12	-1	24	7	NA	12
-19	5	41	4	22	4	-11	-1	22	6	NA	16
-20	5	38	1	24	2	-18	-6	23	6	NA	12
-24	0	39	4	32	8	-17	-2	25	7	NA	19
-29	-5	45	1	27	-2	-15	-7	23	5	NA	13
-28	-4	46	1	27	1	-17	-7	21	5	NA	12
-31	-2	48	2	27	0	-19	-5	21	5	NA	13
-30	-1	48	0	29	1	-11	-10	22	4	NA	11
-32	-8	48	3	38	7	-14	-9	20	4	NA	10
-38	-16	45	6	40	1	-14	-7	22	4	NA	16
-43	-19	44	7	45	0	-13	-9	22	1	NA	12
-51	-28	45	18	50	-3	-15	-9	20	-1	NA	6
-43	-11	45	11	43	0	-15	-10	21	3	NA	8
-43	-4	45	2	44	3	-12	-9	20	4	-22	6
-42	-9	42	-3	44	1	-10	-8	21	3	-26	8
-47	-12	43	3	49	3	-13	-9	21	2	-29	8
-45	-10	50	12	42	2	-13	-10	21	1	-37	9
-38	-2	46	3	36	6	-10	-8	19	4	-34	13
-46	-13	46	2	57	2	-8	-7	21	3	-35	8
-38	0	45	9	42	3	-10	-8	21	5	-36	11
-32	0	49	11	39	9	-14	-6	22	6	-41	8
-27	4	46	9	33	12	-11	-7	19	6	-32	10
-26	7	45	9	32	8	-10	-3	24	6	-40	15
-21	5	49	7	34	7	-13	-6	22	6	-37	12
-23	2	47	8	37	9	-12	-6	22	6	-35	13
-24	-2	45	13	38	11	-10	-4	22	5	-20	12
-17	6	48	11	28	13	-11	-4	24	6	-17	15
-23	-3	51	18	31	9	-12	-7	22	5	-18	13
-16	1	48	14	28	9	-12	-5	23	6	-19	13
-22	0	49	16	30	13	-15	-6	24	5	-20	16
-26	-7	51	19	39	14	-11	-7	21	7	-21	14
-25	-6	54	17	38	16	-15	-4	20	4	-25	12
-21	-4	52	11	39	20	-17	-6	22	5	-23	15
-21	-4	52	11	38	19	-12	-5	23	6	-23	14
-18	-2	53	11	37	18	-14	-3	23	6	-17	19
-12	2	51	14	32	18	-15	-4	22	5	-25	16
-19	-5	55	20	32	19	-15	-6	20	3	-26	16
-31	-15	53	15	44	16	-13	-8	21	2	-17	11
-38	-16	51	13	43	10	-14	-5	21	3	-23	13
-38	-18	52	17	42	11	-14	-7	20	3	-26	12
-32	-13	54	18	38	17	-14	-8	20	2	-37	11
-43	-23	58	25	37	3	-13	-8	17	0	-38	6
-33	-10	57	19	35	14	-13	-6	18	4	-35	9
-28	-10	52	15	37	15	-10	-7	19	4	-36	6
-25	-6	50	14	33	17	-12	-6	19	5	-29	15
-19	-3	53	14	24	20	-9	-2	20	6	-29	17
-20	-4	50	16	24	19	-12	-4	21	6	-29	13
-21	-7	50	19	31	21	-10	-5	20	5	-27	12
-19	-7	51	18	25	17	-10	-2	21	5	-29	13
-17	-7	53	19	28	15	-11	-4	19	3	-24	10
-16	-3	49	20	24	18	-11	-4	22	5	-29	14
-10	0	54	20	25	19	-10	-5	20	5	-21	13
-16	-5	57	24	16	16	-13	-7	18	5	-20	10
-10	-3	58	18	17	21	-10	-5	16	3	-26	11
-8	3	56	15	11	26	-6	-6	17	6	-19	12
-7	2	60	25	12	23	-9	-4	18	6	-22	7
-15	-7	55	23	39	24	-8	-2	19	4	-22	11
-7	-1	54	20	19	23	-12	-3	18	6	-15	9
-6	0	52	20	14	19	-10	0	20	5	-16	13
-6	-3	55	22	15	25	-11	-4	21	4	-22	12
2	4	56	25	7	21	-13	-3	18	5	-21	5
-4	2	54	22	12	19	-10	-3	19	5	-11	13
-4	3	53	26	12	20	-10	-3	19	4	-10	11
-8	0	59	27	14	20	-11	-4	19	3	-6	8
-10	-10	62	41	9	17	-11	-5	21	2	-8	8
-16	-10	63	29	8	25	-11	-5	19	3	-15	8
-14	-9	64	33	4	19	-10	-6	19	2	-16	8
-30	-22	75	39	7	13	-13	-10	17	-1	-24	0
-33	-16	77	27	3	15	-12	-11	16	0	-27	3
-40	-18	79	27	5	15	-13	-13	16	-2	-33	0
-38	-14	77	25	0	13	-15	-12	17	1	-29	-1
-39	-12	82	19	-2	11	-16	-13	16	-2	-34	-1
-46	-17	83	15	6	9	-18	-12	15	-2	-37	-4
-50	-23	81	19	11	2	-17	-15	16	-2	-31	1
-55	-28	78	23	9	-2	-18	-14	16	-6	-33	-1
-66	-31	79	23	17	-4	-20	-16	16	-4	-25	0
-63	-21	79	7	21	-2	-22	-16	18	-2	-27	-1
-56	-19	73	1	21	1	-17	-12	19	0	-21	6
-66	-22	72	7	41	-13	-19	-16	16	-5	-32	0
-63	-22	67	4	57	-11	-18	-15	16	-4	-31	-3
-69	-25	67	-8	65	-14	-26	-17	16	-5	-32	-3
-69	-16	50	-14	68	-4	-19	-15	18	-1	-30	4
-72	-22	45	-10	73	-9	-23	-14	16	-2	-34	1
-69	-21	39	-11	71	-5	-21	-15	15	-4	-35	0
-67	-10	39	-10	71	-4	-27	-14	15	-1	-37	-4
-64	-7	37	-8	70	-8	-27	-16	16	1	-32	-2
-61	-5	30	-8	69	-1	-21	-11	18	1	-28	3
-58	-4	24	-7	65	-2	-22	-14	16	-2	-26	2
-47	7	27	-8	57	-1	-24	-12	19	1	-24	5
-44	6	19	-4	57	8	-21	-11	19	1	-27	6
-42	3	19	3	57	8	-21	-13	18	3	-26	6
-34	10	25	-5	55	6	-22	-12	17	3	-27	3
-38	0	16	-4	65	7	-25	-12	19	1	-27	4
-41	-2	20	5	65	2	-21	-10	22	1	-24	7
-38	-1	25	3	64	3	-26	-12	19	0	-28	5
-37	2	34	6	60	0	-27	-11	19	2	-23	6
-22	8	39	10	43	5	-22	-10	16	2	-23	1
-37	-6	40	16	47	-1	-22	-12	18	-1	-29	3
-36	-4	38	11	40	3	-20	-12	20	1	-25	6
-25	4	42	10	31	4	-21	-11	17	0	-24	0
-15	7	46	21	27	8	-16	-12	17	1	-20	3
-17	3	48	18	24	10	-17	-9	17	1	-22	4
-19	3	51	20	23	14	-19	-6	20	3	-24	7
-12	8	55	18	17	15	-20	-7	21	2	-27	6
-17	3	52	23	16	9	-20	-7	19	0	-25	6
-21	-3	55	28	15	8	-20	-10	18	0	-26	6
-10	4	58	31	8	10	-19	-8	20	3	-24	6
-19	-5	72	38	5	5	-20	-11	17	-2	-26	2
-14	-1	70	27	6	4	-25	-12	15	0	-22	2
-8	5	70	21	5	8	-25	-11	17	1	-20	2
-16	0	63	31	12	8	-22	-11	18	-1	-26	3
-14	-6	66	31	8	10	-19	-9	20	-2	-22	-1
-30	-13	65	29	17	8	-20	-9	19	-1	-29	-4
-33	-15	55	24	22	10	-18	-12	20	-1	-30	4
-37	-8	57	27	24	-8	-17	-10	22	1	-26	5
-47	-20	60	36	36	-6	-17	-10	20	-2	-30	3
-48	-10	63	35	31	-10	-21	-13	21	-5	-33	-1
-50	-22	65	44	34	-15	-17	-13	19	-5	-33	-4
-56	-25	61	39	47	-21	-22	-12	22	-6	-31	0
-47	-10	65	26	33	-24	-24	-14	19	-4	-36	-1
-37	-8	63	27	35	-15	-18	-9	21	-3	-43	-1
-35	-9	59	17	31	-12	-20	-12	19	-3	-40	3
-29	-5	56	20	35	-11	-21	-10	21	-1	-38	2
-28	-7	54	22	39	-11	-17	-13	18	-2	-41	-4
-29	-11	56	32	46	-13	-17	-11	18	-3	-38	-3
-33	-11	54	28	40	-10	-17	-11	20	-3	-40	-1
-41	-16	58	30	50	-9	-21	-11	19	-3	-41	3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Engine error message
Error in if (gqarr[mypoint - kp3 + 1, 2] < 0.01) numsignificant1 <- numsignificant1 +  : 
  missing value where TRUE/FALSE needed
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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Engine error message & 
Error in if (gqarr[mypoint - kp3 + 1, 2] < 0.01) numsignificant1 <- numsignificant1 +  : 
  missing value where TRUE/FALSE needed
Execution halted
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=185704&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Engine error message[/C][C]
Error in if (gqarr[mypoint - kp3 + 1, 2] < 0.01) numsignificant1 <- numsignificant1 +  : 
  missing value where TRUE/FALSE needed
Execution halted
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=185704&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185704&T=0

As an alternative you can also use a 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'Gertrude Mary Cox' @ cox.wessa.net
R Engine error message
Error in if (gqarr[mypoint - kp3 + 1, 2] < 0.01) numsignificant1 <- numsignificant1 +  : 
  missing value where TRUE/FALSE needed
Execution halted



Parameters (Session):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 2 ; 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')
}