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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationMon, 01 Dec 2008 13:25:07 -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/01/t1228163136xcpc7e15mhm8rrf.htm/, Retrieved Sun, 12 May 2024 06:50:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27335, Retrieved Sun, 12 May 2024 06:50:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact254

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]
F RMPD  [Cross Correlation Function] [Q7 - zonder trans...] [2008-12-01 20:04:13] [299afd6311e4c20059ea2f05c8dd029d]
F RM D    [Variance Reduction Matrix] [Q8] [2008-12-01 20:20:44] [299afd6311e4c20059ea2f05c8dd029d]
F    D        [Variance Reduction Matrix] [Q8 - 2] [2008-12-01 20:25:07] [5e2b1e7aa808f9f0d23fd35605d4968f] [Current]
- RM            [Standard Deviation-Mean Plot] [Q8 standard devia...] [2008-12-06 19:18:56] [7d3039e6253bb5fb3b26df1537d500b4]
- RM            [Standard Deviation-Mean Plot] [Verbetering Q7 - 2] [2008-12-08 19:52:58] [299afd6311e4c20059ea2f05c8dd029d]
F RM D          [Standard Deviation-Mean Plot] [Deel 2: Step 1] [2008-12-08 20:09:35] [299afd6311e4c20059ea2f05c8dd029d]
- RM D            [Variance Reduction Matrix] [Deel 2: Step 2 - VRM] [2008-12-08 20:13:17] [299afd6311e4c20059ea2f05c8dd029d]
-                   [Variance Reduction Matrix] [Totale Uitvoer - VRM] [2008-12-17 16:00:59] [299afd6311e4c20059ea2f05c8dd029d]
-  MPD                [Variance Reduction Matrix] [] [2010-12-24 11:50:15] [4dfa50539945b119a90a7606969443b9]
- RM D            [(Partial) Autocorrelation Function] [Deel 2: Step 2 -...] [2008-12-08 20:20:51] [299afd6311e4c20059ea2f05c8dd029d]
- RM D            [(Partial) Autocorrelation Function] [Deel 2: Step 2 - ...] [2008-12-08 20:22:18] [299afd6311e4c20059ea2f05c8dd029d]
-   P               [(Partial) Autocorrelation Function] [Uitvoer vanuit Be...] [2008-12-13 16:33:20] [299afd6311e4c20059ea2f05c8dd029d]
-   P                 [(Partial) Autocorrelation Function] [Uitvoer vanuit Be...] [2008-12-13 16:37:32] [299afd6311e4c20059ea2f05c8dd029d]
-   P                   [(Partial) Autocorrelation Function] [d=0 D=1] [2008-12-14 13:55:01] [299afd6311e4c20059ea2f05c8dd029d]
-   P               [(Partial) Autocorrelation Function] [Totale Uitvoer d=...] [2008-12-17 16:03:30] [299afd6311e4c20059ea2f05c8dd029d]
- RM D            [(Partial) Autocorrelation Function] [Deel 2: Step 2 - ...] [2008-12-08 20:24:54] [299afd6311e4c20059ea2f05c8dd029d]
- RM D            [Spectral Analysis] [Deel 2: Step 2 - ...] [2008-12-08 20:27:07] [299afd6311e4c20059ea2f05c8dd029d]
-   P               [Spectral Analysis] [Totale Uitvoer - ...] [2008-12-17 16:07:59] [299afd6311e4c20059ea2f05c8dd029d]
-  M D                [Spectral Analysis] [Spectral Analysis...] [2010-12-16 10:45:51] [616fb52b46273b7e6805de1e68b3a688]
-  MPD                [Spectral Analysis] [Spectral Analysis...] [2010-12-16 11:12:29] [616fb52b46273b7e6805de1e68b3a688]
-   P                   [Spectral Analysis] [Spectral Analysis...] [2010-12-16 11:14:45] [616fb52b46273b7e6805de1e68b3a688]
-  MPD                [Spectral Analysis] [] [2010-12-24 12:24:57] [4dfa50539945b119a90a7606969443b9]
-  MPD                [Spectral Analysis] [] [2010-12-24 12:35:52] [4dfa50539945b119a90a7606969443b9]
F RM D            [Spectral Analysis] [Deel 2: Step 2 - ...] [2008-12-08 20:29:17] [299afd6311e4c20059ea2f05c8dd029d]
-   P               [Spectral Analysis] [Totale Uitvoer - ...] [2008-12-17 16:10:49] [299afd6311e4c20059ea2f05c8dd029d]
F RM D            [ARIMA Backward Selection] [Deel 2: Step 5] [2008-12-08 20:35:27] [299afd6311e4c20059ea2f05c8dd029d]
-   P               [ARIMA Backward Selection] [Uitvoer vanuit Be...] [2008-12-14 15:42:25] [299afd6311e4c20059ea2f05c8dd029d]
- RMPD                [Multiple Regression] [] [2010-12-21 16:18:28] [1c63f3c303537b65dfa698074d619a3e]
F RMP               [ARIMA Forecasting] [Uitvoer vanuit Be...] [2008-12-14 15:56:40] [299afd6311e4c20059ea2f05c8dd029d]
- RMPD                [ARIMA Forecasting] [Arima Forecasting] [2010-12-28 19:01:32] [74be16979710d4c4e7c6647856088456]
-    D            [Standard Deviation-Mean Plot] [Totale Uitvoer - SMP] [2008-12-17 15:57:12] [299afd6311e4c20059ea2f05c8dd029d]
-  M D              [Standard Deviation-Mean Plot] [Standard Deviatio...] [2010-12-24 13:19:31] [9f313cc7203314d73bf17d2b325aee79]
- RM D              [Variance Reduction Matrix] [Variance Reductio...] [2010-12-24 13:29:11] [9f313cc7203314d73bf17d2b325aee79]
- RMPD              [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2010-12-24 13:35:08] [9f313cc7203314d73bf17d2b325aee79]
- RMPD              [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2010-12-24 13:37:51] [9f313cc7203314d73bf17d2b325aee79]
- RMPD              [Spectral Analysis] [Spectral Analysis] [2010-12-24 13:45:16] [9f313cc7203314d73bf17d2b325aee79]
- RMPD              [Spectral Analysis] [Spectral Analysis] [2010-12-24 13:47:24] [9f313cc7203314d73bf17d2b325aee79]
- RMPD              [Spectral Analysis] [Spectral Analysis] [2010-12-24 13:51:23] [9f313cc7203314d73bf17d2b325aee79]
- RMPD              [ARIMA Backward Selection] [ARIMA Backward Se...] [2010-12-24 14:04:47] [9f313cc7203314d73bf17d2b325aee79]
- RMPD              [ARIMA Forecasting] [ARIMA Forecasting] [2010-12-24 14:15:31] [9f313cc7203314d73bf17d2b325aee79]
- RMPD                [Standard Deviation-Mean Plot] [Standard Deviatio...] [2010-12-27 09:50:14] [9f313cc7203314d73bf17d2b325aee79]
- RMPD                [Variance Reduction Matrix] [Variance Reductio...] [2010-12-27 09:53:20] [9f313cc7203314d73bf17d2b325aee79]
- RMPD                [Spectral Analysis] [Spectral Analysis] [2010-12-27 10:01:30] [9f313cc7203314d73bf17d2b325aee79]
- RMPD                [Spectral Analysis] [Spectral Analysis] [2010-12-27 10:03:10] [9f313cc7203314d73bf17d2b325aee79]
- RMPD                [Classical Decomposition] [Classical Decompo...] [2010-12-27 10:06:19] [9f313cc7203314d73bf17d2b325aee79]
- RMPD                [Decomposition by Loess] [Decomposition by ...] [2010-12-27 10:08:53] [9f313cc7203314d73bf17d2b325aee79]
- RMPD                [ARIMA Backward Selection] [ARIMA Backward Se...] [2010-12-27 10:15:12] [9f313cc7203314d73bf17d2b325aee79]
-   PD                [ARIMA Forecasting] [ARIMA Forecasting] [2010-12-27 10:20:40] [9f313cc7203314d73bf17d2b325aee79]
Feedback Forum
2008-12-06 19:18:31 [Stéphanie Claes] [reply] 
V(Y[t],d=0,D=1) 1264241.30865646
Deze variantie is het kleinste, de student heeft dit fout.
Opnieuw gaan we de seizoenaliteit moeten wegwerken door de D in te stellen op 1.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10772.8
9987.7
8638.7
11063.7
11855.7
10684.5
11337.4
10478
11123.9
12909.3
11339.9
10462.2
12733.5
10519.2
10414.9
12476.8
12384.6
12266.7
12919.9
11497.3
12142
13919.4
12656.8
12034.1
13199.7
10881.3
11301.2
13643.9
12517
13981.1
14275.7
13435
13565.7
16216.3
12970
14079.9
14235
12213.4
12581
14130.4
14210.8
14378.5
13142.8
13714.7
13621.9
15379.8
13306.3
14391.2
14909.9
14025.4
12951.2
14344.3
16213.3
15544.5
14750.6
17292.7
17568.5
17930.8
18644.7
16694.8
17242.8

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27335&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27335&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27335&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Variance Reduction Matrix
V(Y[t],d=0,D=0)4521179.62536612Range10006Trim Var.2642803.07356313
V(Y[t],d=1,D=0)1906817.75581921Range5896.9Trim Var.1362272.61943047
V(Y[t],d=2,D=0)5317011.10014611Range10253.1Trim Var.3734239.33690856
V(Y[t],d=3,D=0)16378077.2865578Range18669.9Trim Var.11270455.4658824
V(Y[t],d=0,D=1)1264241.30865646Range6471.3Trim Var.470177.59
V(Y[t],d=1,D=1)1312501.4310461Range5822.2Trim Var.764630.174053426
V(Y[t],d=2,D=1)4023229.34222017Range10005.2Trim Var.2368564.46837805
V(Y[t],d=3,D=1)13239929.4476908Range18891.5Trim Var.7063141.70589102
V(Y[t],d=0,D=2)3105132.20725225Range8135.5Trim Var.1787147.89632576
V(Y[t],d=1,D=2)1942064.27703968Range6166.3Trim Var.1145149.12479839
V(Y[t],d=2,D=2)5794340.8675126Range10042.8Trim Var.3609586.02464516
V(Y[t],d=3,D=2)19980769.9867825Range17882.3000000000Trim Var.12831597.4425747

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 4521179.62536612 & Range & 10006 & Trim Var. & 2642803.07356313 \tabularnewline
V(Y[t],d=1,D=0) & 1906817.75581921 & Range & 5896.9 & Trim Var. & 1362272.61943047 \tabularnewline
V(Y[t],d=2,D=0) & 5317011.10014611 & Range & 10253.1 & Trim Var. & 3734239.33690856 \tabularnewline
V(Y[t],d=3,D=0) & 16378077.2865578 & Range & 18669.9 & Trim Var. & 11270455.4658824 \tabularnewline
V(Y[t],d=0,D=1) & 1264241.30865646 & Range & 6471.3 & Trim Var. & 470177.59 \tabularnewline
V(Y[t],d=1,D=1) & 1312501.4310461 & Range & 5822.2 & Trim Var. & 764630.174053426 \tabularnewline
V(Y[t],d=2,D=1) & 4023229.34222017 & Range & 10005.2 & Trim Var. & 2368564.46837805 \tabularnewline
V(Y[t],d=3,D=1) & 13239929.4476908 & Range & 18891.5 & Trim Var. & 7063141.70589102 \tabularnewline
V(Y[t],d=0,D=2) & 3105132.20725225 & Range & 8135.5 & Trim Var. & 1787147.89632576 \tabularnewline
V(Y[t],d=1,D=2) & 1942064.27703968 & Range & 6166.3 & Trim Var. & 1145149.12479839 \tabularnewline
V(Y[t],d=2,D=2) & 5794340.8675126 & Range & 10042.8 & Trim Var. & 3609586.02464516 \tabularnewline
V(Y[t],d=3,D=2) & 19980769.9867825 & Range & 17882.3000000000 & Trim Var. & 12831597.4425747 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27335&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]4521179.62536612[/C][C]Range[/C][C]10006[/C][C]Trim Var.[/C][C]2642803.07356313[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1906817.75581921[/C][C]Range[/C][C]5896.9[/C][C]Trim Var.[/C][C]1362272.61943047[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]5317011.10014611[/C][C]Range[/C][C]10253.1[/C][C]Trim Var.[/C][C]3734239.33690856[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]16378077.2865578[/C][C]Range[/C][C]18669.9[/C][C]Trim Var.[/C][C]11270455.4658824[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1264241.30865646[/C][C]Range[/C][C]6471.3[/C][C]Trim Var.[/C][C]470177.59[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1312501.4310461[/C][C]Range[/C][C]5822.2[/C][C]Trim Var.[/C][C]764630.174053426[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]4023229.34222017[/C][C]Range[/C][C]10005.2[/C][C]Trim Var.[/C][C]2368564.46837805[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]13239929.4476908[/C][C]Range[/C][C]18891.5[/C][C]Trim Var.[/C][C]7063141.70589102[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]3105132.20725225[/C][C]Range[/C][C]8135.5[/C][C]Trim Var.[/C][C]1787147.89632576[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1942064.27703968[/C][C]Range[/C][C]6166.3[/C][C]Trim Var.[/C][C]1145149.12479839[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]5794340.8675126[/C][C]Range[/C][C]10042.8[/C][C]Trim Var.[/C][C]3609586.02464516[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]19980769.9867825[/C][C]Range[/C][C]17882.3000000000[/C][C]Trim Var.[/C][C]12831597.4425747[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27335&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27335&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:

Variance Reduction Matrix
V(Y[t],d=0,D=0)4521179.62536612Range10006Trim Var.2642803.07356313
V(Y[t],d=1,D=0)1906817.75581921Range5896.9Trim Var.1362272.61943047
V(Y[t],d=2,D=0)5317011.10014611Range10253.1Trim Var.3734239.33690856
V(Y[t],d=3,D=0)16378077.2865578Range18669.9Trim Var.11270455.4658824
V(Y[t],d=0,D=1)1264241.30865646Range6471.3Trim Var.470177.59
V(Y[t],d=1,D=1)1312501.4310461Range5822.2Trim Var.764630.174053426
V(Y[t],d=2,D=1)4023229.34222017Range10005.2Trim Var.2368564.46837805
V(Y[t],d=3,D=1)13239929.4476908Range18891.5Trim Var.7063141.70589102
V(Y[t],d=0,D=2)3105132.20725225Range8135.5Trim Var.1787147.89632576
V(Y[t],d=1,D=2)1942064.27703968Range6166.3Trim Var.1145149.12479839
V(Y[t],d=2,D=2)5794340.8675126Range10042.8Trim Var.3609586.02464516
V(Y[t],d=3,D=2)19980769.9867825Range17882.3000000000Trim Var.12831597.4425747


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)
sx <- sort(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variance Reduction Matrix',6,TRUE)
a<-table.row.end(a)
for (bigd in 0:2) {
for (smalld in 0:3) {
mylabel <- 'V(Y[t],d='
mylabel <- paste(mylabel,as.character(smalld),sep='')
mylabel <- paste(mylabel,',D=',sep='')
mylabel <- paste(mylabel,as.character(bigd),sep='')
mylabel <- paste(mylabel,')',sep='')
a<-table.row.start(a)
a<-table.element(a,mylabel,header=TRUE)
myx <- x
if (smalld > 0) myx <- diff(x,lag=1,differences=smalld)
if (bigd > 0) myx <- diff(myx,lag=par1,differences=bigd)
a<-table.element(a,var(myx))
a<-table.element(a,'Range',header=TRUE)
a<-table.element(a,max(myx)-min(myx))
a<-table.element(a,'Trim Var.',header=TRUE)
smyx <- sort(myx)
sn <- length(smyx)
a<-table.element(a,var(smyx[smyx>quantile(smyx,0.05) & smyxa<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')