Nothing
## ----include=FALSE------------------------------------------------------------
knitr::knit_hooks$set(time_it = local({
now <- NULL
function(before, options) {
if (before) {
# record the current time before each chunk
now <<- Sys.time()
} else {
# calculate the time difference after a chunk
res <- difftime(Sys.time(), now, units = "secs")
# return a character string to show the time
paste("Time for this code chunk to run:", round(res,
2), "seconds")
}
}
}))
knitr::opts_chunk$set(dev = "png", dev.args = list(type = "cairo-png"), time_it=TRUE)
## ----message=FALSE------------------------------------------------------------
set.seed(1)
library(WeightedCluster)
## ----seqdefbiofam, warning=FALSE, message=FALSE, fig.width=8, fig.height=5----
data(biofam) #load illustrative data
## Defining the new state labels
statelab <- c("Parent", "Left", "Married", "Left/Married", "Child",
"Left/Child", "Left/Married/Child", "Divorced")
## Creating the state sequence object,
biofam.seq <- seqdef(biofam[,10:25], alphabet=0:7, states=statelab)
seqdplot(biofam.seq, legend.prop=0.2)
## ----message=FALSE------------------------------------------------------------
diss <- seqdist(biofam.seq, method="LCS")
## ----fannyclust, warning=FALSE, message=FALSE---------------------------------
library(cluster) ## Loading the library
fclust <- fanny(diss, k=5, diss=TRUE, memb.exp=1.5)
## -----------------------------------------------------------------------------
summary(fclust$membership)
## ----plotfd, fig.width=8, fig.height=5----------------------------------------
## Displaying the resulting clustering with membership threshold of 0.4
fuzzyseqplot(biofam.seq, group=fclust$membership, type="d")
## ----plotf, fig.width=8, fig.height=5-----------------------------------------
## Displaying the resulting clustering with membership threshold of 0.4
fuzzyseqplot(biofam.seq, group=fclust$membership, type="I", membership.threashold =0.4, sortv="membership")
## ----dreg---------------------------------------------------------------------
library(DirichletReg)
##Estimation of Dirichlet Regression
##Dependent variable formatting
fmember <- DR_data(fclust$membership)
## Estimation
bdirig <- DirichReg(fmember~sex+birthyr|1, data=biofam, model="alternative")
## Displaying results of Dirichlet regression.
summary(bdirig)
## ----betareg------------------------------------------------------------------
library(betareg)
## Estimation of beta regression
breg1 <- betareg(fclust$membership[, 3]~sex+birthyr, data=biofam)
## Displaying results
summary(breg1)
## -----------------------------------------------------------------------------
pclust <- seqpropclust(biofam.seq, diss=diss, maxcluster=5, properties=c("state", "duration"))
pclust
## ----eval=FALSE---------------------------------------------------------------
# seqtreedisplay(pclust, type="d", border=NA, showdepth=TRUE)
## -----------------------------------------------------------------------------
pclustqual <- as.clustrange(pclust, diss=diss, ncluster=5)
pclustqual
## ----fig.width=8, fig.height=5------------------------------------------------
seqdplot(biofam.seq, pclustqual$clustering$cluster4)
## ----include=FALSE------------------------------------------------------------
knitr::write_bib(file = 'packages.bib')
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