sptwdglm

R-package for performing Bayesian Variable Selection in Double Generalized Linear Tweedie Spatial Process Models

https://github.com/arh926/sptwdglm

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Keywords

bayesian double-generalized-linear-models spatial-process-models spike-slab-priors tweedie-distribution
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R-package for performing Bayesian Variable Selection in Double Generalized Linear Tweedie Spatial Process Models

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bayesian double-generalized-linear-models spatial-process-models spike-slab-priors tweedie-distribution
Created almost 3 years ago · Last pushed about 1 year ago
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Readme License Citation

README.md

sptwdglm: An R-package for performing Bayesian Variable selection using Spike and Slab priors for Double Generalized Linear Tweedie Spatial Process Models

Maintainer <!-- badges: end -->

sptwdglm contains MCMC algorithms for fitting the following models:

Function | Models :---- | :------------- dglm.autograd.R | Double Generalzied Linear Model (DGLM) ssdglm.autograd.R | Spike and Slab Priors for DGLMs spdglm.autograd.R | Spatial DGLMs spssdglm.autograd.R | Spike and Slab Priors for Spatial DGLMs

Variable selection is performed using the function FDR.R on the model coefficients.

It supplements the paper titled, "Bayesian Variable Selection in Double Generalized Linear Tweedie Spatial Process Models", New England Journal of Statistics in Data Science: Special Issue on Modern Bayesian Methods with Applications in Data Science (https://doi.org/10.51387/23-NEJSDS37).

All of the above MCMC samplers use a Metropolis Adjusted Langevin Algorithm (MALA, see Girolami and Calderhead, 2011 https://rss.onlinelibrary.wiley.com/doi/10.1111/j.1467-9868.2010.00765.x).

Figure showing spatial patterns on the left column and logarithm of aggregated Tweedie response on the right column for 10,000 realizations across 100 locations.

Installation

You can install the development version of sptwdglm like so:

``` r

if you dont have devtools installed

install.packages("devtools")

devtools::install_github("arh926/sptwdglm") ```

Example

There are examples contained within every function. Please install the package to view them.

``` r require(sptwdglm)

non-spatial

mc <- Function(response, mean covariates, dispersion covariates, mcmc parameters)

spatial

mc <- Function(coordinates, response, mean covariates, dispersion covariates, mcmc parameters)

Diagnostics

plot_mcmc(posterior samples)

Variable selection through FDR for coefficients

FDR(mean coefficients) FDR(dispersion coefficients) ```

Owner

  • Name: Aritra Halder
  • Login: arh926
  • Kind: user
  • Location: Philadelphia, PA
  • Company: Drexel University

Assistant Professor of Biostatistics

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Halder"
  given-names: "Aritra"
  orcid: "https://orcid.org/0000-0002-5139-3620"
title: "sptwdglm"
version: 1.0.0
doi:
date-released: 2023-04-10
url: "https://github.com/arh926/sptwdglm"

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