# sample_posterior_R: sample from the posterior R distribution In annecori/EpiEstim: Estimate Time Varying Reproduction Numbers from Epidemic Curves

## Description

sample from the posterior R distribution

## Usage

 `1` ```sample_posterior_R(R, n = 1000, window = 1L) ```

## Arguments

 `R` an `estimate_R` object from the estimate_r function function. `n` an integer specifying the number of samples to be taken from the gamma distribution. `window` an integer (or sequence of integers) specifying the window(s) from which to estimate R. Defaults to the first window. If multiple windows are specified, the resulting samples will be drawn from several distributions.

## Value

n values of R from the posterior R distribution

Anne Cori

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```## load data on pandemic flu in a school in 2009 data("Flu2009") ## estimate the reproduction number (method "non_parametric_si") ## when not specifying t_start and t_end in config, they are set to estimate ## the reproduction number on sliding weekly windows res <- estimate_R(incid = Flu2009\$incidence, method = "non_parametric_si", config = make_config(list(si_distr = Flu2009\$si_distr))) ## Sample R from the first weekly window win <- 1L R_median <- res\$R\$`Median(R)`[win] R_CrI <- c(res\$R\$`Quantile.0.025(R)`[win], res\$R\$`Quantile.0.975(R)`[win]) set.seed(2019-06-06) # fixing the random seed for reproducibility R_sample <- sample_posterior_R(res, n = 1000, window = win) hist(R_sample, col = "grey", main = "R sampled from the first weekly window") abline(v = R_median, col = "red") # show the median estimated R abline(v = R_CrI, col = "red", lty = 2) # show the 95%CrI of R ```

annecori/EpiEstim documentation built on May 4, 2021, 9:41 a.m.