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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_partial_least_squares.wasp

Title produced by software

Partial Least Squares - Path Modeling

Date of computation

Tue, 11 Dec 2012 06:06:21 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/11/t1355223993fo94niboumnfxsw.htm/, Retrieved Wed, 24 Apr 2024 21:15:21 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198412, Retrieved Wed, 24 Apr 2024 21:15:21 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

118

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Partial Least Squares - Path Modeling] [Comp10 deel2] [2012-12-11 11:06:21] [18c3d79a4e145c2d06829f66a34e03f3] [Current]

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Dataseries X:

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Histogram

Boxplots

18.2	2687	1870	1890	145.7	352.2
143.8	13271	9115	8190	-279.0	83.0
23.4	13621	4848	4572	485.0	898.9
1.1	3614	367	90	14.1	24.6
49.5	6425	6131	2448	345.8	682.5
4.8	1022	1754	1370	72.0	119.5
20.8	1093	1679	1070	100.9	164.5
19.4	1529	1295	444	25.6	137.0
2.1	2788	271	304	23.5	28.9
79.4	19788	9084	10636	1092.9	2576.8
2.8	327	542	959	54.1	72.5
3.8	1117	1038	478	59.7	91.7
4.1	5401	550	376	25.6	37.5
13.2	1128	1516	430	-47.0	26.7
2.8	1633	701	679	74.3	135.9
48.5	44736	16197	4653	-732.5	-651.9
6.2	5651	1254	2002	310.7	407.9
10.8	5835	4053	1601	-93.8	173.8
3.8	278	205	853	44.8	50.5
21.9	5074	2557	1892	239.9	578.3
12.6	866	1487	944	71.7	115.4
128.0	4418	8793	4459	283.6	456.5
87.3	6914	7029	7957	400.6	754.7
16.0	862	1601	1093	66.9	106.8
0.7	401	176	1084	55.6	57.0
22.5	430	1155	1045	55.7	70.8
15.4	799	1140	683	57.6	89.2
3.0	4789	453	367	40.2	51.4
2.1	2548	264	181	22.2	26.2
4.1	5249	527	346	37.8	56.2
6.4	3494	1653	1442	160.9	320.3
26.6	1804	2564	483	70.5	164.9
304.0	26432	28285	33172	2336.0	3562.0
18.6	623	2247	797	57.0	93.8
65.0	1608	6615	829	56.1	134.0
66.2	4662	4781	2988	28.7	371.5
83.0	5769	6571	9462	482.0	792.0
62.0	6259	4152	3090	283.7	524.5
1.6	1654	451	779	84.8	130.4
400.2	52634	50056	95697	6555.0	9874.0
23.3	999	1878	393	-173.5	-108.1
4.6	1679	1354	687	93.8	154.6
164.6	4178	17124	2091	180.8	390.4
1.9	223	557	1040	60.6	63.7
57.5	6307	8199	598	-771.5	-524.3
2.4	3720	356	211	26.6	34.8
77.3	3442	5080	2673	235.4	361.5
15.8	33406	3222	1413	201.7	246.7
0.6	1257	355	181	167.5	304.0
3.5	1743	597	717	121.6	172.4
9.0	12505	1302	702	108.4	131.4
62.0	3940	4317	3940	315.2	566.3
7.4	8998	882	988	93.0	119.0
15.6	21419	2516	930	107.6	164.7
25.2	2366	3305	1117	131.2	256.5
25.4	2448	3484	1036	48.8	257.1
3.5	1440	1617	639	81.7	126.4
27.3	14045	15636	2754	418.0	1462.0
37.5	4084	4346	3023	302.7	521.7
3.4	3010	749	1120	146.3	209.2
14.3	1286	1734	361	69.2	145.7
6.1	707	706	275	61.4	77.8
4.9	3086	1739	1507	202.7	335.2
3.3	252	312	883	41.7	60.6
7.0	11052	1097	606	64.9	97.6
8.2	9672	1037	829	92.6	118.2
43.5	1112	3689	542	30.3	96.9
48.5	1104	5123	910	63.7	133.3
5.4	478	672	866	67.1	101.6
49.5	10348	5721	1915	223.6	322.5
29.1	2769	3725	663	-208.4	12.4
2.6	752	2149	101	11.1	15.2
0.8	4989	518	53	-3.1	-0.3
184.8	10528	14992	5377	312.7	710.7
2.3	1995	2662	341	34.7	100.7
8.0	2286	2235	2306	195.3	219.0
10.3	952	1307	309	35.4	92.8
50.0	2957	2806	457	40.6	93.5
118.1	2535	5958	1921	177.0	288.0

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	vre.aston.ac.uk @ vre.aston.ac.uk

\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 & 0 seconds \tabularnewline
R Server & vre.aston.ac.uk @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198412&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]vre.aston.ac.uk @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198412&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198412&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	vre.aston.ac.uk @ vre.aston.ac.uk

Parameters (Session):

par1 = Aantalwerknemers Totaleactiva omzet marktwaarde winst cashflow ;

Parameters (R input):

R code (references can be found in the software module):

library(plspm)
library(diagram)
y <- as.data.frame(t(y))
is.data.frame(y)
head(y)
trim <-	function(char) {
return(sub('s+$', '', sub('^s+', '', char)))
}
(latnames <- strsplit(par1,' ')[[1]])
(n <- length(latnames))
(L1 <- as.numeric(strsplit(par3,' ')[[1]]))
(L2 <- as.numeric(strsplit(par4,' ')[[1]]))
(L3 <- as.numeric(strsplit(par5,' ')[[1]]))
(L4 <- as.numeric(strsplit(par6,' ')[[1]]))
(L5 <- as.numeric(strsplit(par7,' ')[[1]]))
(L6 <- as.numeric(strsplit(par8,' ')[[1]]))
(L7 <- as.numeric(strsplit(par9,' ')[[1]]))
(L8 <- as.numeric(strsplit(par10,' ')[[1]]))
(S1 <- as.numeric(strsplit(par11,' ')[[1]]))
(S2 <- as.numeric(strsplit(par12,' ')[[1]]))
(S3 <- as.numeric(strsplit(par13,' ')[[1]]))
(S4 <- as.numeric(strsplit(par14,' ')[[1]]))
(S5 <- as.numeric(strsplit(par15,' ')[[1]]))
(S6 <- as.numeric(strsplit(par16,' ')[[1]]))
(S7 <- as.numeric(strsplit(par17,' ')[[1]]))
(S8 <- as.numeric(strsplit(par18,' ')[[1]]))
if (n==1) sat.mat <- rbind(S1)
if (n==2) sat.mat <- rbind(S1,S2)
if (n==3) sat.mat <- rbind(S1,S2,S3)
if (n==4) sat.mat <- rbind(S1,S2,S3,S4)
if (n==5) sat.mat <- rbind(S1,S2,S3,S4,S5)
if (n==6) sat.mat <- rbind(S1,S2,S3,S4,S5,S6)
if (n==7) sat.mat <- rbind(S1,S2,S3,S4,S5,S6,S7)
if (n==8) sat.mat <- rbind(S1,S2,S3,S4,S5,S6,S7,S8)
sat.mat
if (n==1) sat.sets <- list(L1)
if (n==2) sat.sets <- list(L1,L2)
if (n==3) sat.sets <- list(L1,L2,L3)
if (n==4) sat.sets <- list(L1,L2,L3,L4)
if (n==5) sat.sets <- list(L1,L2,L3,L4,L5)
if (n==6) sat.sets <- list(L1,L2,L3,L4,L5,L6)
if (n==7) sat.sets <- list(L1,L2,L3,L4,L5,L6,L7)
if (n==8) sat.sets <- list(L1,L2,L3,L4,L5,L6,L7,L8)
sat.sets
(sat.mod <- strsplit(par2,' ')[[1]])
res <- plspm(x=y, sat.mat, sat.sets, sat.mod, scheme='centroid', scaled=TRUE, boot.val=TRUE)
(r <- summary(res))
myr <- res$path.coefs
myind <- 1
for (j in 1:(length(sat.mat[1,])-1)) {
for (i in 1:length(sat.mat[,1])) {
if (sat.mat[i,j] == 1) {
if ((res$boot$path[myind,'perc.05'] < 0) && (res$boot$path[myind,'perc.95'] > 0)) {
myr[i,j] = 0
}
myind = myind + 1
}
}
}
bitmap(file='test1.png')
plotmat(round(myr,4), pos = NULL, curve = 0, name = latnames,
lwd = 1, box.lwd = 1, cex.txt = 1, box.type = 'circle',
box.prop = 0.5, box.cex = 1, arr.type = 'triangle',
arr.pos = 0.5, shadow.size = 0.01, prefix = '', arr.lcol = 'blue',
arr.col = 'blue', arr.width = 0.2, main = c('Inner Model',
'Path Coefficients'))
dev.off()
myr <- res$path.coefs
myind <- 1
myi <- 1
for (j in 1:(length(sat.mat[1,])-1)) {
for (i in 1:length(sat.mat[,1])) {
if (i > j) {
myr[i,j] = res$boot$total.efs[myi,'Original']
myi = myi + 1
if ((res$boot$total.efs[myind,'perc.05'] < 0) && (res$boot$total.efs[myind,'perc.95'] > 0)) {
myr[i,j] = 0
}
myind = myind + 1
}
}
}
bitmap(file='test2.png')
plotmat(round(myr,4), pos = NULL, curve = 0, name = latnames,
lwd = 1, box.lwd = 1, cex.txt = 1, box.type = 'circle',
box.prop = 0.5, box.cex = 1, arr.type = 'triangle',
arr.pos = 0.5, shadow.size = 0.01, prefix = '', arr.lcol = 'blue',
arr.col = 'blue', arr.width = 0.2, main = c('Inner Model',
'Total Effects'))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'PARTIAL LEAST SQUARES PATH MODELING (PLS-PM)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'MODEL SPECIFICATION',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of Cases',header=TRUE)
a<-table.element(a,r$xxx$obs)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Latent Variables',header=TRUE)
a<-table.element(a,n)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Manifest Variables',header=TRUE)
a<-table.element(a,length(y[1,]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Scaled?',header=TRUE)
a<-table.element(a,r$xxx$scaled)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Weighting Scheme',header=TRUE)
a<-table.element(a,r$xx$scheme)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bootstrapping?',header=TRUE)
a<-table.element(a,r$xx$boot.val)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bootstrap samples',header=TRUE)
a<-table.element(a,r$xx$br)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BLOCKS DEFINITION',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
a<-table.element(a,'Type',header=TRUE)
a<-table.element(a,'NMVs',header=TRUE)
a<-table.element(a,'Mode',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],header=TRUE)
a<-table.element(a,r$input$Type[i])
a<-table.element(a,r$unidim$MVs[i])
a<-table.element(a,r$unidim$Type.measure[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BLOCKS UNIDIMENSIONALITY',7,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
a<-table.element(a,'Type.measure',header=TRUE)
a<-table.element(a,'MVs',header=TRUE)
a<-table.element(a,'eig.1st',header=TRUE)
a<-table.element(a,'eig.2nd',header=TRUE)
a<-table.element(a,'C.alpha',header=TRUE)
a<-table.element(a,'DG.rho',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],header=TRUE)
a<-table.element(a,r$unidim$Type.measure[i])
a<-table.element(a,r$unidim$MVs[i])
a<-table.element(a,r$unidim$eig.1st[i])
a<-table.element(a,r$unidim$eig.2nd[i])
a<-table.element(a,r$unidim$C.alpha[i])
a<-table.element(a,r$unidim$DG.rho[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'OUTER MODEL',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
a<-table.element(a,'weights',header=TRUE)
a<-table.element(a,'std.loads',header=TRUE)
a<-table.element(a,'communal',header=TRUE)
a<-table.element(a,'redundan',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],5,header=TRUE)
a<-table.row.end(a)
for (j in 1:length(r$outer.mod[[i]][,1])) {
a<-table.row.start(a)
a<-table.element(a,rownames(r$outer.mod[[i]])[j],header=T)
a<-table.element(a,r$outer.mod[[i]][j,1])
a<-table.element(a,r$outer.mod[[i]][j,2])
a<-table.element(a,r$outer.mod[[i]][j,3])
a<-table.element(a,r$outer.mod[[i]][j,4])
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'CORRELATIONS BETWEEN MVs AND LVs',n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
for (iii in 1:n) {
a<-table.element(a,latnames[iii],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],n+1,header=TRUE)
a<-table.row.end(a)
for (j in 1:length(r$outer.cor[[i]][,1])) {
a<-table.row.start(a)
a<-table.element(a,rownames(r$outer.cor[[i]])[j],header=T)
for (iii in 1:n) {
a<-table.element(a,r$outer.cor[[i]][j,iii])
}
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,'INNER MODEL',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Block',header=TRUE)
a<-table.element(a,'Concept',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
for (i in 1:(length(labels(r$inner.mod)))) {
a<-table.row.start(a)
print (paste('i=',i,sep=''))
a<-table.element(a,labels(r$inner.mod)[i],3,header=TRUE)
a<-table.row.end(a)
for (j in 1:length(r$inner.mod[[i]][,1])) {
print (paste('j=',j,sep=''))
a<-table.row.start(a)
a<-table.element(a,rownames(r$inner.mod[[i]])[j],header=T)
a<-table.element(a,r$inner.mod[[i]][j,1],header=T)
a<-table.element(a,r$inner.mod[[i]][j,2])
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable6.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'CORRELATIONS BETWEEN LVs',n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (iii in 1:n) {
a<-table.element(a,latnames[iii],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],header=T)
for (j in 1:n) {
a<-table.element(a,r$latent.cor[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable7.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'SUMMARY INNER MODEL',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'LV.Type',header=TRUE)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'MVs',header=TRUE)
a<-table.element(a,'R.square',header=TRUE)
a<-table.element(a,'Av.Commu',header=TRUE)
a<-table.element(a,'Av.Redun',header=TRUE)
a<-table.element(a,'AVE',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,latnames[i],header=T)
a<-table.element(a,r$inner.sum[i,1])
a<-table.element(a,r$inner.sum[i,2])
a<-table.element(a,r$inner.sum[i,3])
a<-table.element(a,r$inner.sum[i,4])
a<-table.element(a,r$inner.sum[i,5])
a<-table.element(a,r$inner.sum[i,6])
a<-table.element(a,r$inner.sum[i,7])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable8.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'GOODNESS-OF-FIT',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'GoF',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
for (i in 1:4) {
a<-table.row.start(a)
a<-table.element(a,r$gof[i,1],header=T)
a<-table.element(a,r$gof[i,2])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable9.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TOTAL EFFECTS',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'relationships',header=TRUE)
a<-table.element(a,'dir.effect',header=TRUE)
a<-table.element(a,'ind.effect',header=TRUE)
a<-table.element(a,'tot.effect',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(r$effects[,1])) {
a<-table.row.start(a)
a<-table.element(a,r$effects[i,1],header=T)
a<-table.element(a,r$effects[i,2])
a<-table.element(a,r$effects[i,3])
a<-table.element(a,r$effects[i,4])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable10.tab')
dum <- r$boot$weights
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - WEIGHTS',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable11.tab')
dum <- r$boot$loadings
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - LOADINGS',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable12.tab')
dum <- r$boot$paths
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - PATHS',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable13.tab')
dum <- r$boot$rsq
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - RSQ',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable14.tab')
dum <- r$boot$total.efs
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'BOOTSTRAP VALIDATION - TOTAL EFFECTS',length(colnames(dum))+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
for (i in 1:length(colnames(dum))) {
a<-table.element(a,colnames(dum)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:length(rownames(dum))) {
a<-table.row.start(a)
a<-table.element(a,rownames(dum)[i],header=T)
for (j in 1:length(colnames(dum))) {
a<-table.element(a,dum[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable15.tab')
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Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code