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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 02 Dec 2008 10:47:16 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/02/t1228240089dcniwjhhjeimz91.htm/, Retrieved Fri, 17 May 2024 03:05:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28142, Retrieved Fri, 17 May 2024 03:05:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [Standard Deviation-Mean Plot] [Q5 Randow walk task] [2008-11-29 13:16:45] [6743688719638b0cb1c0a6e0bf433315]
F         [Standard Deviation-Mean Plot] [Q5 ] [2008-11-29 15:18:13] [de72ca3f4fcfd0997c84e1ac92aea119]
F    D        [Standard Deviation-Mean Plot] [Q8 Workshop 4] [2008-12-02 17:47:16] [56fd94b954e08a6655cb7790b21ee404] [Current]
F   PD          [Standard Deviation-Mean Plot] [Q8 Workshop 4] [2008-12-02 17:57:26] [de72ca3f4fcfd0997c84e1ac92aea119]
- RMPD            [(Partial) Autocorrelation Function] [] [2008-12-06 16:30:23] [74be16979710d4c4e7c6647856088456]
- RMPD            [Spectral Analysis] [] [2008-12-06 16:31:48] [74be16979710d4c4e7c6647856088456]
F RMPD          [Cross Correlation Function] [Q9 Workshop 4] [2008-12-02 18:02:55] [de72ca3f4fcfd0997c84e1ac92aea119]
-   P             [Cross Correlation Function] [] [2008-12-06 16:38:31] [74be16979710d4c4e7c6647856088456]
-   P             [Cross Correlation Function] [verbeterd] [2008-12-09 18:02:40] [74be16979710d4c4e7c6647856088456]
Feedback Forum
2008-12-06 16:22:50 [Ken Wright] [reply] 
goed, de lambda gaat de spreiding zo stationair mogelijk maken
2008-12-08 17:41:08 [Birgit Van Dyck] [reply] 
De tabel geeft de optimale lambda waarde weer om de tijdreeks te modelleren, stationaier maken. Een tijdreeks stationair maken betekent dat de trend er wordt uit gehaald en de spreiding en het niveau gelijk wordt.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,9059
0,8883
0,8924
0,8833
0,87
0,8758
0,8858
0,917
0,9554
0,9922
0,9778
0,9808
0,9811
1,0014
1,0183
1,0622
1,0773
1,0807
1,0848
1,1582
1,1663
1,1372
1,1139
1,1222
1,1692
1,1702
1,2286
1,2613
1,2646
1,2262
1,1985
1,2007
1,2138
1,2266
1,2176
1,2218
1,249
1,2991
1,3408
1,3119
1,3014
1,3201
1,2938
1,2694
1,2165
1,2037
1,2292
1,2256
1,2015
1,1786
1,1856
1,2103
1,1938
1,202
1,2271
1,277
1,265
1,2684
1,2811
1,2727
1,2611
1,2881
1,3213
1,2999
1,3074
1,3242
1,3516
1,3511
1,3419
1,3716
1,3622
1,3896
1,4227
1,4684

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28142&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28142&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28142&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.9187250.04515488748337620.1222
21.083633333333330.06009093613899360.1852
31.216591666666670.02962534106695370.0954
41.271708333333330.0457043355479410.1371
51.230258333333330.03961033975051860.102500000000000
61.330833333333330.03740870908159640.128500000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.918725 & 0.0451548874833762 & 0.1222 \tabularnewline
2 & 1.08363333333333 & 0.0600909361389936 & 0.1852 \tabularnewline
3 & 1.21659166666667 & 0.0296253410669537 & 0.0954 \tabularnewline
4 & 1.27170833333333 & 0.045704335547941 & 0.1371 \tabularnewline
5 & 1.23025833333333 & 0.0396103397505186 & 0.102500000000000 \tabularnewline
6 & 1.33083333333333 & 0.0374087090815964 & 0.128500000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28142&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]0.918725[/C][C]0.0451548874833762[/C][C]0.1222[/C][/ROW]
[ROW][C]2[/C][C]1.08363333333333[/C][C]0.0600909361389936[/C][C]0.1852[/C][/ROW]
[ROW][C]3[/C][C]1.21659166666667[/C][C]0.0296253410669537[/C][C]0.0954[/C][/ROW]
[ROW][C]4[/C][C]1.27170833333333[/C][C]0.045704335547941[/C][C]0.1371[/C][/ROW]
[ROW][C]5[/C][C]1.23025833333333[/C][C]0.0396103397505186[/C][C]0.102500000000000[/C][/ROW]
[ROW][C]6[/C][C]1.33083333333333[/C][C]0.0374087090815964[/C][C]0.128500000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28142&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28142&T=1

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


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

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.9187250.04515488748337620.1222
21.083633333333330.06009093613899360.1852
31.216591666666670.02962534106695370.0954
41.271708333333330.0457043355479410.1371
51.230258333333330.03961033975051860.102500000000000
61.330833333333330.03740870908159640.128500000000000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0791705808258452
beta-0.0308333301500609
S.D.0.0305130816029635
T-STAT-1.01049545081236
p-value0.369418618925884

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0791705808258452 \tabularnewline
beta & -0.0308333301500609 \tabularnewline
S.D. & 0.0305130816029635 \tabularnewline
T-STAT & -1.01049545081236 \tabularnewline
p-value & 0.369418618925884 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28142&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0791705808258452[/C][/ROW]
[ROW][C]beta[/C][C]-0.0308333301500609[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0305130816029635[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.01049545081236[/C][/ROW]
[ROW][C]p-value[/C][C]0.369418618925884[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28142&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28142&T=2

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


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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0791705808258452
beta-0.0308333301500609
S.D.0.0305130816029635
T-STAT-1.01049545081236
p-value0.369418618925884






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.05493630260437
beta-0.75583035803014
S.D.0.785698211768153
T-STAT-0.961985590280526
p-value0.390533220558701
Lambda1.75583035803014

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.05493630260437 \tabularnewline
beta & -0.75583035803014 \tabularnewline
S.D. & 0.785698211768153 \tabularnewline
T-STAT & -0.961985590280526 \tabularnewline
p-value & 0.390533220558701 \tabularnewline
Lambda & 1.75583035803014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28142&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.05493630260437[/C][/ROW]
[ROW][C]beta[/C][C]-0.75583035803014[/C][/ROW]
[ROW][C]S.D.[/C][C]0.785698211768153[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.961985590280526[/C][/ROW]
[ROW][C]p-value[/C][C]0.390533220558701[/C][/ROW]
[ROW][C]Lambda[/C][C]1.75583035803014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28142&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28142&T=3

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


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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.05493630260437
beta-0.75583035803014
S.D.0.785698211768153
T-STAT-0.961985590280526
p-value0.390533220558701
Lambda1.75583035803014


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')