Parametric Bootstrap or Resample a projection matrix Workflow

None

sink(output)
print(input)

library(popbio)
max_num<-max(y)
png(output)
hist(y, br=30, col="palegreen", xlab="Lambda", plot=TRUE,
	xlim=c(0, max_num), main=plottitle)
abline(v=ci, lty=3)
dev.off()

sink(output)
print(input)

sink(output)
print(input)

sink(output)
print(input)

stageData <- read.table(stageMatrixFile)
stageMatrix <- as.matrix(stageData)
dimnames(stageMatrix) <- list(stages,stages)

indices = match(some_values, all_values)

indices = match(some_values, all_values)

Name	Description
stageMatrixFile	Here comes the stage matrix without the stage names (as you see in the example). It should be provied as a txt-file. Example from: J. Gerard B. Oostermeijer; M.L. Brugman; E.R. de Boer; H.C.M. Den Nijs. 1996. Temporal and Spatial Variation in the Demography of Gentiana pneumonanthe, a Rare Perennial Herb. The Journal of Ecology, Vol. 84(2): 153-166.
abundances	In this dialogue appear the fields with the initial abundance per stage observed in the field. As an example Gentiana pneumonanthe has 5 stages with its respective abundance. The abundance of the stages or categories must be added one by one. First press Add value, fill the abundance of the first stage and press enter; then press Add value and fill once again the next stage abundance; repeat the action until you have fill all the abundance of all stages. Stage abundance of the year 1987: 1) S (seedlings) 69 2) J (Juveniles) 100 3) V (vegetative) 111 4) G (reproductive individuals) 21 5) D (dormant plants) 43
iterations	Number of iterations for calculation of the resample analysis of the parametric Bootstrap. Click in Set Value, tip the number in the right window.
stages	Here come the names of the stages or categories of the input matrix. It is very important that the stages names are not longer than 8 characters. The name of the stages must be added one by one. The respective name stages must be filled one by one. First press add value, fill a stage name (not longer than 8 characters) and press enter, then press add value and fill once again the next stage name, repeat the action until you have fill all the stages names. In the following example, the matrix has 5 stages or categories: S J V G D S 0.0000 0.0000 0.0000 7.6660 0.0000 J 0.0579 0.0100 0.0000 8.5238 0.0000 V 0.4637 0.8300 0.9009 0.2857 0.8604 G 0.0000 0.0400 0.0090 0.6190 0.1162 D 0.0000 0.0300 0.0180 0.0000 0.0232 The stages of this matrix are called: 1) Seedlings S 2) Juveniles J 3) Vegetative V 4) Reproductive individuals G 5) Dormant plants D
plotTitle	Descriptive title for labelling generated output graph. Click in Set Value, tip the text in the right window. e.g.: Gentiana pneumonanthe, Terschelling (species taxonomic name, place where the research was conducted)

Name	Type	Description
display	rshell	Script sink(output) print(input) R Server localhost:6311
plot_histogram	rshell	Script library(popbio) max_num<-max(y) png(output) hist(y, br=30, col="palegreen", xlab="Lambda", plot=TRUE, xlim=c(0, max_num), main=plottitle) abline(v=ci, lty=3) dev.off() R Server localhost:6311
display_2	rshell	Script sink(output) print(input) R Server localhost:6311
display_3	rshell	Script sink(output) print(input) R Server localhost:6311
display_4	rshell	Script sink(output) print(input) R Server localhost:6311
Workflow32	workflow
StageMatrix_ReadFromFile	rshell	Script stageData <- read.table(stageMatrixFile) stageMatrix <- as.matrix(stageData) dimnames(stageMatrix) <- list(stages,stages) R Server localhost:6311
CategoriseStages_Interaction	interaction	With this dialogue automatically appears the names of the stages or categories of the census data file. When the dialogue appears, the stages are in disorder, so the user drags and organizes the stages according to the order in the life cycle. Then, the author chooses if the stage belongs to the recruited, reproductive category or it should be excluded. Recruited means that new individuals can be recruited to this (these) stage(s). Reproductive stages are those that reproduce (produce offspring) (in this example the stage G). In the census data file Dt1.txt, x is use to denote when a plant has died in the second year, so the user must selected in the excluded column. Then the user clicks in confirm and you will read stages submitted. In the following example, the life cycle of Gentiana pneumonanthe has 5 stages or categories: 1) Seedlings S 2) Juveniles J 3) Vegetative V 4) Reproductive individuals G 5) Dormant plants D Interaction Page http://biovel.googlecode.com/svn/trunk/popmod/mpm/select_stages.html
FecundityCols_FromReproductiveStages	rshell	Script indices = match(some_values, all_values) R Server localhost:6311
FecundityRows_FromRecruitedStages	rshell	Script indices = match(some_values, all_values) R Server localhost:6311

Name	Description
histogram	Histogram plotting the frequencies of the lambda values and the 95% confidence intervals resulting from the bootstrap analysis.
lambda	Lambda (λ) or dominant eigenvalue, this value describes the population growth rate of a stage matrix. The population will be stable, grow or decrease at a rate given by lambda: e.g.: Lambda (λ) = 1 (population is stable), Lambda (λ) > 1 (population is growing) and finally Lambda (λ) < 1 (population is decreasing).
x	X= List of resampled matrices it is the list of matrices generated by bootstrap analysis and the number of the matrices at the same time is based on the number of itineration’s.
mean	The mean matrix is calculated based on the matrices generated by bootstrap analysis and the number of the matrices at the same time is based on the number of itineration’s.
variance	The variance matrix is calculated based on the matrices generated by bootstrap analysis and the number of the matrices at the same time is based on the number of itineration’s.
confidence_interval	95% Confidence interval of Lambda. In statistics, a confidence interval (CI) is a type of interval estimate of a population parameter and is used to indicate the reliability of an estimate. It is an observed interval (i.e. it is calculated from the observations), in principle different from sample to sample, that frequently includes the parameter of interest if the experiment is repeated. How frequently the observed interval contains the parameter is determined by the confidence level or confidence coefficient

Source	Sink
Workflow32:confidence_interval	display:input
Workflow32:confidence_interval	plot_histogram:ci
plotTitle	plot_histogram:plottitle
Workflow32:y	plot_histogram:y
Workflow32:x	display_2:input
Workflow32:mean	display_3:input
Workflow32:variance	display_4:input
iterations	Workflow32:iterations
abundances	Workflow32:abundances
StageMatrix_ReadFromFile:stageMatrix	Workflow32:stage_matrix
FecundityRows_FromRecruitedStages:indices	Workflow32:frows
FecundityCols_FromReproductiveStages:indices	Workflow32:fcols
stages	StageMatrix_ReadFromFile:stages
stageMatrixFile	StageMatrix_ReadFromFile:stageMatrixFile
stages	CategoriseStages_Interaction:unsortedStages
CategoriseStages_Interaction:sortedStages	FecundityCols_FromReproductiveStages:all_values
CategoriseStages_Interaction:reproductiveStages	FecundityCols_FromReproductiveStages:some_values
CategoriseStages_Interaction:sortedStages	FecundityRows_FromRecruitedStages:all_values
CategoriseStages_Interaction:recruitedStages	FecundityRows_FromRecruitedStages:some_values
plot_histogram:output	histogram
Workflow32:lambda	lambda
display_2:output	x
display_3:output	mean
display_4:output	variance
display:output	confidence_interval

Parametric Bootstrap or Resample a projection matrix Workflow

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