bellreg - Count Regression Models Based on the Bell Distribution

Bell regression models for count data with overdispersion. The implemented models account for ordinary and zero-inflated regression models under both frequentist and Bayesian approaches. Theoretical details regarding the models implemented in the package can be found in Castellares et al. (2018) <doi:10.1016/j.apm.2017.12.014> and Lemonte et al. (2020) <doi:10.1080/02664763.2019.1636940>.

Last updated 1 months ago

5.28 score 1 packages 21 scripts 728 downloads

survstan - Fitting Survival Regression Models via 'Stan'

Parametric survival regression models under the maximum likelihood approach via 'Stan'. Implemented regression models include accelerated failure time (AFT) models, proportional hazards (PH) models, proportional odds (PO) models, accelerated hazard (AH) models, Yang and Prentice (YP) models, and extended hazard (EH) models. Available baseline survival distributions include exponential, Weibull, log-normal, log-logistic, gamma, generalized gamma, rayleigh, Gompertz and fatigue (Birnbaum-Saunders) distributions. The baseline survival distribution can be further modeled using Bernstein polynomails' approximation of the baseline hazard function. References: Lawless (2002) <ISBN:9780471372158>; Bennett (1982) <doi:10.1002/sim.4780020223>; Chen and Wang(2000) <doi:10.1080/01621459.2000.10474236>; Demarqui and Mayrink (2021) <doi:10.1214/20-BJPS471>.

Last updated 3 months ago

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4.84 score 2 stars 63 scripts 245 downloads

YPPE - Yang and Prentice Model with Piecewise Exponential Baseline Distribution

Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with piecewise exponential baseline distribution. Details about the model can be found in Demarqui and Mayrink (2021) <doi:10.1214/20-BJPS471>. Model fitting carried out via likelihood-based and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.

Last updated 1 years ago

cpp

4.48 score 3 stars 8 scripts 142 downloads

rsurv - Random Generation of Survival Data

Random generation of survival data from a wide range of regression models, including accelerated failure time (AFT), proportional hazards (PH), proportional odds (PO), accelerated hazard (AH), Yang and Prentice (YP), and extended hazard (EH) models. The package 'rsurv' also stands out by its ability to generate survival data from an unlimited number of baseline distributions provided that an implementation of the quantile function of the chosen baseline distribution is available in R. Another nice feature of the package 'rsurv' lies in the fact that linear predictors are specified via a formula-based approach, facilitating the inclusion of categorical variables and interaction terms. The functions implemented in the package 'rsurv' can also be employed to simulate survival data with more complex structures, such as survival data with different types of censoring mechanisms, survival data with cure fraction, survival data with random effects (frailties), multivariate survival data, and competing risks survival data. Details about the R package 'rsurv' can be found in Demarqui (2024) <doi:10.48550/arXiv.2406.01750>.

Last updated 1 months ago

4.38 score 1 stars 24 scripts 527 downloads

covid19br - Brazilian COVID-19 Pandemic Data

Set of functions to import COVID-19 pandemic data into R. The Brazilian COVID-19 data, obtained from the official Brazilian repository at <https://covid.saude.gov.br/>, is available at country, region, state, and city-levels. The package also downloads the world-level COVID-19 data from the John Hopkins University's repository.

Last updated 1 years ago

brazilcovid-19

3.90 score 4 stars 40 scripts 413 downloads

peppm - Piecewise Exponential Distribution with Random Time Grids

Fits the Piecewise Exponential distribution with random time grids using the clustering structure of the Product Partition Models. Details of the implemented model can be found in Demarqui et al. (2008) <doi:10.1007/s10985-008-9086-0>.

Last updated 4 years ago

cpp

2.70 score 5 scripts 115 downloads

YPBP - Yang and Prentice Model with Baseline Distribution Modeled by Bernstein Polynomials

Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with baseline hazard/odds modeled with Bernstein polynomials. Details about the model can be found in Demarqui et al. (2019) <arXiv:1910.04475>. Model fitting can be carried out via both maximum likelihood and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.

Last updated 4 years ago

cpp

2.00 score 10 scripts 153 downloads