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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_fitdistrweibull.wasp
Title produced by softwareMaximum-likelihood Fitting - Weibull Distribution
Date of computationWed, 24 Aug 2016 00:23:54 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Aug/24/t1471995233mbfpr0pdgwljlg8.htm/, Retrieved Mon, 29 Apr 2024 21:35:54 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Mon, 29 Apr 2024 21:35:54 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsForensic Alcohol Proficiency test by CDPH, pool July 2016, CA crime laboratories, proficiency testing, blood alcohol
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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'Gertrude Mary Cox' @ cox.wessa.net






ParameterEstimated ValueStandard Deviation
shape19.28937341999921.0387035667597
scale0.1191822974535950.00064387231539247

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
shape & 19.2893734199992 & 1.0387035667597 \tabularnewline
scale & 0.119182297453595 & 0.00064387231539247 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]shape[/C][C]19.2893734199992[/C][C]1.0387035667597[/C][/ROW]
[ROW][C]scale[/C][C]0.119182297453595[/C][C]0.00064387231539247[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

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

ParameterEstimated ValueStandard Deviation
shape19.28937341999921.0387035667597
scale0.1191822974535950.00064387231539247


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 30 ; par2 = 40 ;
Parameters (R input):
par1 = 30 ; par2 = 40 ;
R code (references can be found in the software module):
par2 <- '50'
par1 <- '20'
library(MASS)
PPCCWeibull <- function(shape, scale, x)
{
x <- sort(x)
pp <- ppoints(x)
cor(qweibull(pp, shape=shape, scale=scale), x)
}
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1 < 0.1) par1 <- 0.1
if (par1 > 50) par1 <- 50
if (par2 < 0.1) par2 <- 0.1
if (par2 > 50) par2 <- 50
par1h <- par1*10
par2h <- par2*10
sortx <- sort(x)
c <- array(NA,dim=c(par2h))
for (i in par1h:par2h)
{
c[i] <- cor(qweibull(ppoints(x), shape=i/10,scale=2),sortx)
}
bitmap(file='test1.png')
plot((par1h:par2h)/10,c[par1h:par2h],xlab='shape',ylab='correlation',main='PPCC Plot - Weibull')
dev.off()
f<-fitdistr(x, 'weibull')
f$estimate
f$sd
xlab <- paste('Weibull(shape=',round(f$estimate[[1]],2))
xlab <- paste(xlab,', scale=')
xlab <- paste(xlab,round(f$estimate[[2]],2))
xlab <- paste(xlab,')')
bitmap(file='test2.png')
qqplot(qweibull(ppoints(x), shape=f$estimate[[1]], scale=f$estimate[[2]]), x, main='QQ plot (Weibull)', xlab=xlab )
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Parameter',1,TRUE)
a<-table.element(a,'Estimated Value',1,TRUE)
a<-table.element(a,'Standard Deviation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'shape',header=TRUE)
a<-table.element(a,f$estimate[1])
a<-table.element(a,f$sd[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'scale',header=TRUE)
a<-table.element(a,f$estimate[2])
a<-table.element(a,f$sd[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')