fdabl

library('doParallel')
registerDoParallel(cores = 4)


#' Spike-and-Slab Regression using Gibbs Sampling for p > 1 predictors
#'
#' @param y: vector of responses
#' @param X: matrix of predictor values
#' @param nr_samples: indicates number of samples drawn
#' @param a1: parameter a1 of Gamma prior on variance sigma2e

fdabl

library(ggplot2)
library(RColorBrewer)

# Roughly estimates the number of Covid infectious people at an ADE party(N = 900)
# Main uncertainties:
#   (1) Number of people infectious
#   (2) Number of people a single infectious person infects (R_eff)
#
# For (1), we rely on the number of positive tests from last week. This was 1.5%. Generally, this is an underestimate
# of the true number. Similarly, many people are coming to ADE abroad. We use a distribution over different values below.

fdabl

library(ggplot2)
library(RColorBrewer)

# Roughly estimates the number of Covid infectious people at an ADE party(N = 900)
# Main uncertainties:
#   (1) Number of people infectious
#   (2) Number of people a single infectious person infects (R_eff)
#
# For (1), we rely on the number of positive tests from last week. This was 1.5%. Generally, this is an underestimate
# of the true number. Similarly, many people are coming to ADE abroad. We use a distribution over different values below.

fdabl

library(ggplot2)
library(RColorBrewer)

# Roughly estimates the number of Covid infectious people at an ADE party(N = 900)
# Main uncertainties:
#   (1) Number of people infectious
#   (2) Number of people a single infectious person infects (R_eff)
#
# For (1), we rely on the number of positive tests from last week. This was 1.5%. Generally, this is an underestimate
# of the true number. Similarly, many people are coming to ADE abroad. We use a distribution over different values below.

fdabl

library(ggplot2)
library(RColorBrewer)

# Roughly estimates the number of Covid infectious people at an ADE party(N = 900)
# Main uncertainties:
#   (1) Number of people infectious
#   (2) Number of people a single infectious person infects (R_eff)
#
# For (1), we rely on the number of positive tests from last week. This was 1.5%. Generally, this is an underestimate
# of the true number. Similarly, many people are coming to ADE abroad. We use a distribution over different values below.

fdabl

library(ggplot2)
library(RColorBrewer)

# Roughly estimates the risk of getting Covid by attending an ADE party(N = 900)
# Main uncertainties:
#   (1) Number of people infectious
#   (2) Number of people a single infectious person infects (R_eff)
#
# For (1), we rely on the number of positive tests from last week. This was 1.5%. Generally, this is an underestimate
# of the true number. Similarly, many people are coming to ADE abroad. We use a distribution over different values below.

fdabl

library(ggplot2)
library(RColorBrewer)

# Roughly estimates the risk of getting Covid by attending an ADE party(N = 900)
# Main uncertainties:
#   (1) Number of people infectious
#   (2) Number of people a single infectious person infects (R_eff)
#
# For (1), we rely on the number of positive tests from last week. This was 1.5%. Generally, this is an underestimate
# of the true number. Similarly, many people are coming to ADE abroad. We use a distribution over different values below.