R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
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]
[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 05 Aug. 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
quickcode
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
dhReg
Dynamic Harmonic Regression
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Pranay Gaikwad (view profile)
noisyr
Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput
sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Ilias Moutsopoulos (view profile)
dcov
A Fast Implementation of Distance Covariance
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Hang Weiqiang (view profile)
kernelPSI
Post-Selection Inference for Nonlinear Variable Selection
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Lotfi Slim (view profile)
28,083
R Packages
239,283
Dependencies
74,457
Author Associations
28,084
Publication Badges
