Nothing
## ---- echo = FALSE------------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width=7,
fig.height=5
)
## ----install, eval=FALSE------------------------------------------------------
# install.packages("incidence")
## ----install2, eval=FALSE-----------------------------------------------------
# devtools::install_github("reconhub/incidence")
## ---- data--------------------------------------------------------------------
library(outbreaks)
library(ggplot2)
library(incidence)
dat <- ebola_sim$linelist$date_of_onset
class(dat)
head(dat)
## ---- incid1------------------------------------------------------------------
i <- incidence(dat)
i
plot(i)
## ---- interv------------------------------------------------------------------
# weekly, starting on Monday (ISO week, default)
i.7 <- incidence(dat, interval = "1 week")
plot(i.7)
# semi-weekly, starting on Saturday
i.14 <- incidence(dat, interval = "2 saturday weeks")
plot(i.14, border = "white")
## monthly
i.month <- incidence(dat, interval = "1 month")
plot(i.month, border = "white")
## ---- gender------------------------------------------------------------------
i.7.sex <- incidence(dat, interval = "1 week", groups = ebola_sim$linelist$gender)
i.7.sex
plot(i.7.sex, stack = TRUE, border = "grey")
## ---- hosp--------------------------------------------------------------------
i.7.hosp <- with(ebola_sim_clean$linelist,
incidence(date_of_onset, interval = "week", groups = hospital))
i.7.hosp
head(get_counts(i.7.hosp))
plot(i.7.hosp, stack=TRUE) +
theme(legend.position= "top") +
labs(fill="")
## ---- middle------------------------------------------------------------------
i[100:250]
plot(i[100:250])
## ---- stripes-----------------------------------------------------------------
i.7[c(TRUE,FALSE)]
plot(i.7[c(TRUE,FALSE)])
## ---- tail--------------------------------------------------------------------
i.tail <- subset(i, from=as.Date("2015-01-01"))
i.tail
plot(i.tail, border="white")
## ---- i7outcome---------------------------------------------------------------
i.7.outcome <- incidence(dat, 7, groups=ebola_sim$linelist$outcome)
i.7.outcome
plot(i.7.outcome, stack = TRUE, border = "grey")
## ---- groupsub----------------------------------------------------------------
i.7.outcome[,1:2]
plot(i.7.outcome[,1:2], stack = TRUE, border = "grey")
## ---- pool--------------------------------------------------------------------
i.pooled <- pool(i.7.outcome)
i.pooled
identical(i.7$counts, i.pooled$counts)
## ---- fit1--------------------------------------------------------------------
plot(i.7[1:20])
early.fit <- fit(i.7[1:20])
early.fit
## -----------------------------------------------------------------------------
plot(early.fit)
## -----------------------------------------------------------------------------
plot(i.7[1:20], fit = early.fit)
## ---- fit.both----------------------------------------------------------------
fit.both <- fit(i.7, split=as.Date("2014-10-15"))
fit.both
plot(i.7, fit=fit.both)
## ---- optim-------------------------------------------------------------------
best.fit <- fit_optim_split(i.7)
best.fit
plot(i.7, fit=best.fit$fit)
## ---- get_info----------------------------------------------------------------
get_info(best.fit$fit, "doubling") # doubling time
get_info(best.fit$fit, "doubling.conf") # confidence interval
get_info(best.fit$fit, "halving")
get_info(best.fit$fit, "halving.conf")
## ---- optim2------------------------------------------------------------------
best.fit2 <- fit_optim_split(i.7.sex)
best.fit2
plot(i.7.sex, fit=best.fit2$fit)
## ---- get_info_groups---------------------------------------------------------
get_info(best.fit2$fit, "doubling") # doubling time
get_info(best.fit2$fit, "doubling.conf") # confidence interval
get_info(best.fit2$fit, "halving")
get_info(best.fit2$fit, "halving.conf")
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