:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Watson, Samuel I
Format:	Preprint
Published:	2024
Subjects:	Computation
Online Access:	https://arxiv.org/abs/2403.09448
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FunctionalCalibration: an R package for estimation in aggregated functional data model
by: Sousa, Alex Rodrigo dos Santos, et al.
Published: (2026)

stelfi: An R package for fitting Hawkes and log‐Gaussian Cox point process models
by: Charlotte M. Jones‐Todd, et al.
Published: (2024)

Log-Gaussian Cox Processes on General Metric Graphs
by: Bolin, David, et al.
Published: (2025)

Log Gaussian Cox Process Background Modeling in High Energy Physics
by: Frid, Yuval, et al.
Published: (2025)

Generalised Linear Mixed Model Specification, Analysis, Fitting, and Optimal Design in R with the glmmr Packages
by: Watson, Samuel I.
Published: (2023)

Bayesian inference for case-control point pattern data in spatial epidemiology with the \texttt{inlabru} R package
by: Palmí-Perales, Francisco, et al.
Published: (2025)

Log-Gaussian Cox Processes for Spatiotemporal Traffic Fatality Estimation in Addis Ababa
by: Abebe, Yassin Tesfaw, et al.
Published: (2024)

Exact Bayesian Gaussian Cox Processes Using Random Integral
by: Tang, Bingjing, et al.
Published: (2024)

iLBA: An R package for confidentially disseminating aggregated frequency tables
by: Hwang, Jeehyun, et al.
Published: (2026)

A Log-Gaussian Cox Process with Sequential Monte Carlo for Line Narrowing in Spectroscopy
by: Härkönen, Teemu, et al.
Published: (2022)

Efficient estimation of Cox model with random change point
by: Xuerong Chen, et al.
Published: (2024)

Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes
by: D'Angelo, Nicoletta, et al.
Published: (2022)

deepspat: An R package for modeling nonstationary spatial and spatio-temporal Gaussian and extremes data through deep deformations
by: Vu, Quan, et al.
Published: (2025)

Extending the saemix package for R to fit non Gaussian outcomes
by: Comets, Emmanuelle, et al.
Published: (2026)

Monitoring data in R with the lumberjack package
by: van der Loo, Mark P. J.
Published: (2020)

Estimating Velocities of Infectious Disease Spread Through Spatio‐Temporal Log‐Gaussian Cox Point Processes
by: Fernando Rodriguez Avellaneda, et al.
Published: (2026)

Gaussian spatial regression using the spmoran package: case study examples
by: Murakami, Daisuke
Published: (2017)

Scalable likelihood-based estimation and variable selection for the Cox model with incomplete covariates
by: Kwok, Ngok Sang, et al.
Published: (2024)

Neuronal functional connectivity graph estimation with the R package neurofuncon
by: Beede, Lauren Miako, et al.
Published: (2024)

GPTreeO: An R package for continual regression with dividing local Gaussian processes
by: Braun, Timo, et al.
Published: (2024)

regMMD: An R package for parametric estimation and regression with maximum mean discrepancy
by: Alquier, Pierre, et al.
Published: (2025)

Gratia: An R package for exploring generalized additive models
by: Simpson, Gavin L.
Published: (2024)

pintervals: an R package for model-agnostic prediction intervals
by: Randahl, David, et al.
Published: (2026)

Calibrar: an R package for fitting complex ecological models
by: Oliveros-Ramos, Ricardo, et al.
Published: (2016)

Meta-analysis with the glmmTMB R package
by: Williams, Coralie, et al.
Published: (2026)

Gaussian process modelling of infectious diseases using the Greta software package and GPUs
by: Gunn, Eva, et al.
Published: (2024)

Semiparametric fiducial inference for Cox models
by: Cui, Yifan, et al.
Published: (2024)

Inference for Log-Gaussian Cox Point Processes using Bayesian Deep Learning: Application to Human Oral Microbiome Image Data
by: Wang, Shuwan, et al.
Published: (2025)

piCurve: an R package for modeling photosynthesis-irradiance curves
by: Amirian, Mohammad M., et al.
Published: (2025)

‘mixglm': an R package for estimation of stable states, tipping points, and ecosystem resilience using mixture models
by: Adam Klimeš, et al.
Published: (2025)

Introducing the vfunc R package
by: Hankin, Robin K. S.
Published: (2026)

modelimportance: An R package for evaluating model importance within a multi-model ensemble
by: Kim, Minsu, et al.
Published: (2026)

An introduction to R package `mvs`
by: van Loon, Wouter
Published: (2025)

Log-concave density estimation in undirected graphical models
by: Kubjas, Kaie, et al.
Published: (2022)

Spatio-temporal Shared-Field Modeling of Beluga and Bowhead Whale Sightings Using a Joint Marked Log-Gaussian Cox Process
by: Pant, Mauli, et al.
Published: (2025)

Bayesian multilevel compositional data analysis with the R package multilevelcoda
by: Le, Flora, et al.
Published: (2024)

MacBehaviour: An R package for behavioural experimentation on large language models
by: Duan, Xufeng, et al.
Published: (2024)

Efficient ensemble uncertainty estimation in Gaussian Processes Regression
by: Christiansen, Mads-Peter Verner, et al.
Published: (2024)

Spatially continuous modelling of aggregated outcome data
by: Villejo, Stephen Jun, et al.
Published: (2026)

rollama: An R package for using generative large language models through Ollama
by: Gruber, Johannes B., et al.
Published: (2024)