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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationTue, 02 Dec 2008 08:21:33 -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/t1228231534j8c8zjiayktjum7.htm/, Retrieved Sun, 19 May 2024 08:48:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27946, Retrieved Sun, 19 May 2024 08:48:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsjulie govaerts
Estimated Impact176

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Variance Reduction Matrix] [eigen gegevens] [2008-12-02 15:21:33] [02bc582261bca489735616f51251e20c] [Current]
Feedback Forum
2008-12-06 13:36:27 [Thomas Plasschaert] [reply] 
goede bewerkingen en conclusies genomen
2008-12-07 12:23:43 [Jolien Van Landeghem] [reply] 
Juist, maar je had ook nog de heteroskedasticiteit kunnen berekenen. Dit door naar de plot (variance reduction matrix) te kijken of gewoon naar de p value. Als deze kleiner is dan 0.05 is er sprake van heteroskedasticiteit (variantie wordt groter naarmate de tijd vordert) en deze gaan we wegwerken door de data tot de gevonden lambda waarde te verheffenen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
345
334
345
333
336
324
320
330
313
301
288
294
302
294
293
290
283
286
293
334
329
411
416
418
408
402
401
400
389
371
364
350
332
323
316
312
315
314
313
314
317
308
312
306
304
297
284
278
273
265
259
252
245
235
232
229
219
218
215
211

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=27946&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=27946&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27946&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)2734.51836158192Range207Trim Var.1905.94968553459
V(Y[t],d=1,D=0)204.649327878434Range100Trim Var.35.3621190130624
V(Y[t],d=2,D=0)377.125529340593Range164Trim Var.68.8280542986425
V(Y[t],d=3,D=0)1265.35213032581Range297Trim Var.218.607058823529
V(Y[t],d=0,D=1)5121.78546099291Range234Trim Var.3549.92804878049
V(Y[t],d=1,D=1)545.950971322849Range185Trim Var.81.45
V(Y[t],d=2,D=1)752.021739130435Range160Trim Var.142.794230769231
V(Y[t],d=3,D=1)2413.49797979798Range315Trim Var.519.883940620783
V(Y[t],d=0,D=2)14954.2944444444Range390Trim Var.12000.8225806452
V(Y[t],d=1,D=2)1861.28235294118Range278Trim Var.328.206451612903
V(Y[t],d=2,D=2)2421.70499108734Range315Trim Var.641.058620689655
V(Y[t],d=3,D=2)7859.5643939394Range536Trim Var.2339.0960591133

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 2734.51836158192 & Range & 207 & Trim Var. & 1905.94968553459 \tabularnewline
V(Y[t],d=1,D=0) & 204.649327878434 & Range & 100 & Trim Var. & 35.3621190130624 \tabularnewline
V(Y[t],d=2,D=0) & 377.125529340593 & Range & 164 & Trim Var. & 68.8280542986425 \tabularnewline
V(Y[t],d=3,D=0) & 1265.35213032581 & Range & 297 & Trim Var. & 218.607058823529 \tabularnewline
V(Y[t],d=0,D=1) & 5121.78546099291 & Range & 234 & Trim Var. & 3549.92804878049 \tabularnewline
V(Y[t],d=1,D=1) & 545.950971322849 & Range & 185 & Trim Var. & 81.45 \tabularnewline
V(Y[t],d=2,D=1) & 752.021739130435 & Range & 160 & Trim Var. & 142.794230769231 \tabularnewline
V(Y[t],d=3,D=1) & 2413.49797979798 & Range & 315 & Trim Var. & 519.883940620783 \tabularnewline
V(Y[t],d=0,D=2) & 14954.2944444444 & Range & 390 & Trim Var. & 12000.8225806452 \tabularnewline
V(Y[t],d=1,D=2) & 1861.28235294118 & Range & 278 & Trim Var. & 328.206451612903 \tabularnewline
V(Y[t],d=2,D=2) & 2421.70499108734 & Range & 315 & Trim Var. & 641.058620689655 \tabularnewline
V(Y[t],d=3,D=2) & 7859.5643939394 & Range & 536 & Trim Var. & 2339.0960591133 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27946&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]2734.51836158192[/C][C]Range[/C][C]207[/C][C]Trim Var.[/C][C]1905.94968553459[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]204.649327878434[/C][C]Range[/C][C]100[/C][C]Trim Var.[/C][C]35.3621190130624[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]377.125529340593[/C][C]Range[/C][C]164[/C][C]Trim Var.[/C][C]68.8280542986425[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1265.35213032581[/C][C]Range[/C][C]297[/C][C]Trim Var.[/C][C]218.607058823529[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]5121.78546099291[/C][C]Range[/C][C]234[/C][C]Trim Var.[/C][C]3549.92804878049[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]545.950971322849[/C][C]Range[/C][C]185[/C][C]Trim Var.[/C][C]81.45[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]752.021739130435[/C][C]Range[/C][C]160[/C][C]Trim Var.[/C][C]142.794230769231[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]2413.49797979798[/C][C]Range[/C][C]315[/C][C]Trim Var.[/C][C]519.883940620783[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]14954.2944444444[/C][C]Range[/C][C]390[/C][C]Trim Var.[/C][C]12000.8225806452[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1861.28235294118[/C][C]Range[/C][C]278[/C][C]Trim Var.[/C][C]328.206451612903[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]2421.70499108734[/C][C]Range[/C][C]315[/C][C]Trim Var.[/C][C]641.058620689655[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]7859.5643939394[/C][C]Range[/C][C]536[/C][C]Trim Var.[/C][C]2339.0960591133[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27946&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27946&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)2734.51836158192Range207Trim Var.1905.94968553459
V(Y[t],d=1,D=0)204.649327878434Range100Trim Var.35.3621190130624
V(Y[t],d=2,D=0)377.125529340593Range164Trim Var.68.8280542986425
V(Y[t],d=3,D=0)1265.35213032581Range297Trim Var.218.607058823529
V(Y[t],d=0,D=1)5121.78546099291Range234Trim Var.3549.92804878049
V(Y[t],d=1,D=1)545.950971322849Range185Trim Var.81.45
V(Y[t],d=2,D=1)752.021739130435Range160Trim Var.142.794230769231
V(Y[t],d=3,D=1)2413.49797979798Range315Trim Var.519.883940620783
V(Y[t],d=0,D=2)14954.2944444444Range390Trim Var.12000.8225806452
V(Y[t],d=1,D=2)1861.28235294118Range278Trim Var.328.206451612903
V(Y[t],d=2,D=2)2421.70499108734Range315Trim Var.641.058620689655
V(Y[t],d=3,D=2)7859.5643939394Range536Trim Var.2339.0960591133


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')