backnow_cm {linelistBayes}R Documentation

Get Bayesian Back-calculation Estimates and Model Diagnostics

Description

This function performs Bayesian back-calculation, imputation of missing delays, and nowcasting based on the provided data.

Usage

backnow_cm(
  outcome,
  days,
  week,
  weekend,
  iter,
  sigma,
  maxdelay,
  si,
  size,
  workerID,
  printProgress,
  cd = NULL
)

Arguments

outcome

Vector of outcomes; difference between report and onset times

days

Vector of days when the report is given, aligned from the minimum report day

week

Vector indicating the week of the report, assumes no change within the week

weekend

Binary vector indicating if the outcome was reported during a weekend

iter

Number of iterations for the Bayesian back-calculation algorithm

sigma

The standard deviation for the normal distribution

maxdelay

The maximum delay parameter for the negative binomial distribution

si

Serial interval vector

size

The size parameter for the negative binomial distribution

workerID

Identifier for the parallel worker

printProgress

Flag to print the progress information

cd

second size parameter, unused

Value

output A list object that contains the back-calculated estimates and model diagnostics

Examples


data("sample_onset_dates")
data("sample_report_dates")
line_list <- create_linelist(sample_report_dates, sample_onset_dates)
sip <- si(14, 4.29, 1.18)
results <- run_backnow(
 line_list, 
  MAX_ITER = as.integer(2000), 
  norm_sigma = 0.5, 
  sip = sip,
  NB_maxdelay = as.integer(20), 
  NB_size = as.integer(6), 
  workerID = 1, 
  printProgress = 1, 
 preCalcTime = TRUE)


[Package linelistBayes version 1.0 Index]