library("markovchain")
## Function to create a simplex
runif_simplex <- function(T) {
x <- -log(runif(T))
x / sum(x)
}
clinicalStates <- c("healthy", "recurrent", "dead")
clinicalMatrix <- matrix(c(runif_simplex(K), c(0, runif_simplex(K-1)), c(0,0, 1) ), nrow = 3, byrow = TRUE)
mcClinical <- new("markovchain", states = clinicalStates,
byrow = TRUE, transitionMatrix = clinicalMatrix,
name = "Clinical")
plot(mcClinical, main="Clinical Markov Chain")
initialState <- c(1, 0, 0)
#multiplication
after2Days <- initialState * (mcClinical * mcClinical)
after2Days
mcClinical^2
as(mcClinical, "data.frame")
transientStates(mcClinical)
absorbingStates(mcClinical)
resultsOfDay <- rmarkovchain(n = 50, object = mcClinical, t0 = "healthy")
resultsOfDay
McFitMle <- markovchainFit(data = resultsOfDay,method = "bootstrap", name = "Clinical Markov Chain")
McFitMle
markovchainFit(data = rain$rain, method = "mle", name = "Alofi")
data(rain)
rain$rain[1:10]
createSequenceMatrix(stringchar = rain$rain)
library("msSurv")
data("RCdata")
RCdata[70:76, ]
Nodes <- c("1", "2", "3", "4", "5")
Edges <- list("1" = list(edges = c("2", "3")),
"2" = list(edges = c("4", "5")),
"3" = list(edges = NULL),
"4" = list(edges = NULL),
"5" = list(edges = NULL))
treeobj <- new("graphNEL", nodes = Nodes, edgeL = Edges,
edgemode = "directed")
ex1 <- msSurv(RCdata, treeobj, bs = TRUE)
Pst(ex1, s = 1, t = 3.1)
Pst(ex1, s = 1, t = 3.1, covar = TRUE)
SOPt(ex1, t = 0.85)
SOPt(ex1, t = 0.85, covar = TRUE)
data("LTRCdata")
Nodes <- c("1", "2", "3")
Edges <- list("1" = list(edges = c("2", "3")),
"2" = list(edges = c("3")),
"3" = list(edges = NULL))
LTRCtree <- new("graphNEL", nodes = Nodes, edgeL = Edges,
edgemode = "directed")
ex2 <- msSurv(LTRCdata, LTRCtree, LT = TRUE)
summary(ex2)
if(exists("data.sdc")) head(data.sdc)
data(data.sdc)
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