Other packages > Find by keyword >

GPRMortality  

Gaussian Process Regression for Mortality Rates
View on CRAN: Click here


Download and install GPRMortality package within the R console
Install from CRAN:
install.packages("GPRMortality")

Install from Github:
library("remotes")
install_github("cran/GPRMortality")

Install by package version:
library("remotes")
install_version("GPRMortality", "0.1.0")



Attach the package and use:
library("GPRMortality")
Maintained by
Ali Ghanbari
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-08-26
Latest Update: 2018-08-26
Description:
A Bayesian statistical model for estimating child (under-five age group) and adult (15-60 age group) mortality. The main challenge is how to combine and integrate these different time series and how to produce unified estimates of mortality rates during a specified time span. GPR is a Bayesian statistical model for estimating child and adult mortality rates which its data likelihood is mortality rates from different data sources such as: Death Registration System, Censuses or surveys. There are also various hyper-parameters for completeness of DRS, mean, covariance functions and variances as priors. This function produces estimations and uncertainty (95% or any desirable percentiles) based on sampling and non-sampling errors due to variation in data sources. The GP model utilizes Bayesian inference to update predicted mortality rates as a posterior in Bayes rule by combining data and a prior probability distribution over parameters in mean, covariance function, and the regression model. This package uses Markov Chain Monte Carlo (MCMC) to sample from posterior probability distribution by 'rstan' package in R. Details are given in Wang H, Dwyer-Lindgren L, Lofgren KT, et al. (2012) , Wang H, Liddell CA, Coates MM, et al. (2014) and Mohammadi, Parsaeian, Mehdipour et al. (2017) .
How to cite:
Ali Ghanbari (2018). GPRMortality: Gaussian Process Regression for Mortality Rates. R package version 0.1.0, https://cran.r-project.org/web/packages/GPRMortality. Accessed 26 Oct. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited GPRMortality R package
View GPRMortality citation profile
Other R packages that GPRMortality depends, imports, suggests or enhances
Complete documentation for GPRMortality
Functions, R codes and Examples using the GPRMortality R package
Some associated functions: GPRMortality . GPRMortalityChild . GPRMortalitySummary . data.mean.child . data.mean . data.mortality.child . data.mortality . 
Some associated R codes: GPRMortality.R . GPRMortalitySummary.R . GPRMortality_child.R .  Full GPRMortality package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

rts2  
Log-Gaussian Cox Process Models with Approximations
Supports modelling real-time case data to facilitate the real-time surveillance of infectious disea ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
LSDsensitivity  
Sensitivity Analysis Tools for 'LSD' Simulations
Tools for sensitivity analysis of LSD simulation models. Reads object-oriented data produced by LSD ...
Download / Learn more Package Citations See dependency  
SADEG  
Stability Analysis in Differentially Expressed Genes
We analyzed the nucleotide composition of genes with a special emphasis on stability of DNA sequence ...
Download / Learn more Package Citations See dependency  
MARSS  
Multivariate Autoregressive State-Space Modeling
The MARSS package provides maximum-likelihood parameter estimation for constrained and unconstraine ...
Download / Learn more Package Citations See dependency  

29,218

R Packages

247,686

Dependencies

77,281

Author Associations

29,219

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA