| Name : R-GPRMortality
| |
| Version : 0.1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.5.1
| Date : 2024-09-17 12:51:47
|
| Group : Development/Libraries/Other
| Source RPM : R-GPRMortality-0.1.0-lp153.5.1.src.rpm
|
| Size : 0.51 MB
| |
| Packager : (none)
| |
| Summary : Gaussian Process Regression for Mortality Rates
|
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) < doi:10.1016/S0140-6736(12)61719-X>, Wang H,
Liddell CA, Coates MM, et al. (2014)
< doi:10.1016/S0140-6736(14)60497-9> and Mohammadi, Parsaeian, Mehdipour
et al. (2017) < doi:10.1016/S2214-109X(17)30105-5>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
