Welcome to ClientVPS Mirrors

Getting Started with BayesianFitForecast

Getting Started with BayesianFitForecast

Introduction

BayesianFitForecast provides robust tools for parameter estimation and forecasting with epidemiological models. These tools are designed to streamline the process of analyzing epidemiological data using Bayesian inference. Detailed guidance on how to set up an option file can be found in the documentation available here: https://arxiv.org/abs/2411.05371.


Basic Usage

Running the MCMC Analysis

Below is a demonstration of how to set up and run the MCMC analysis, followed by analyzing the results.

# Specify the path to the data file (for Run_analyzeResults). The data file will be generated by Run_MCMC.

data_file <- system.file("extdata", package = "BayesianFitForecast")

# Specify the path to the option file.
option_file <- system.file("extdata", "option.R", 
                           package = "BayesianFitForecast")

# Specify the path to the Excel file including the reported data.
excel_file <- system.file("extdata", "SanFrancisco.xlsx", 
                          package = "BayesianFitForecast") 
# Specify the path to save the results. By default, it is set to the temporary path. 
output_path <- tempdir()

# Run the MCMC analysis. It generates the .Rdata file (data_file).
Run_MCMC(option_file, excel_file, output_path)

# Analyze the results. It generates all results files within a folder. 
Run_analyzeResults(data_file, option_file, excel_file, output_path)

# Please note that you can specify any address to data_file, option_file, excel_file, and output_path.

Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.

This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.