Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
dpi = 300,
fig.width = 5, fig.height = 3
)
## ----message = FALSE, warning=FALSE, eval = TRUE------------------------------
library(cfr)
# packages to wrangle and plot data
library(dplyr)
## ----message = FALSE, warning = FALSE, eval = TRUE----------------------------
data("ebola1976")
# view the first few rows
head(ebola1976)
df_ebola_subset <- filter(ebola1976, date <= "1976-09-30")
## -----------------------------------------------------------------------------
# calculate known death outcomes
df_estimated_outcomes_ebola <- estimate_outcomes(
data = df_ebola_subset,
delay_density = function(x) dgamma(x, shape = 2.40, scale = 3.33)
)
# print head of data frame
head(df_estimated_outcomes_ebola)
# print tail of data frame
tail(df_estimated_outcomes_ebola)
## ----message = FALSE, warning = FALSE, eval = TRUE----------------------------
# calculating the naive CFR
cfr_static(
data = df_ebola_subset
)
# calculating the corrected CFR
cfr_static(
df_ebola_subset,
delay_density = function(x) dgamma(x, shape = 2.40, scale = 3.33)
)
## -----------------------------------------------------------------------------
# get Covid data loaded with the package
data("covid_data")
# filter for the U.K
df_covid_uk <- filter(
covid_data,
country == "United Kingdom", date <= "2020-12-31"
)
# View the first few rows and recall necessary columns: date, cases, deaths
head(df_covid_uk)
## ----message = FALSE, warning = FALSE, eval = TRUE----------------------------
# calculating the naive CFR
cfr_static(
df_covid_uk
)
# calculating the corrected CFR
cfr_static(
df_covid_uk,
delay_density = function(x) dlnorm(x, meanlog = 2.577, sdlog = 0.440)
)
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