kppmenet: combining the kppm and elastic net regularization for inhomogeneous Cox point process with correlated covariates
A Choiruddin, T Yuni Susanto, A Husain… - Journal of Applied …, 2024 - Taylor & Francis
The kppm is a standard procedure to estimate the parameters of the inhomogeneous Cox
point process. However, the procedure cannot handle the problem when the models involve …
point process. However, the procedure cannot handle the problem when the models involve …
COVID-19 transmission risk in Surabaya and Sidoarjo: an inhomogeneous marked Poisson point process approach
Understanding the spatio-temporal dynamics of COVID-19 transmission is necessary to plan
better strategies for controlling the spread of the disease. However, only a few studies …
better strategies for controlling the spread of the disease. However, only a few studies …
[PDF][PDF] On the earthquake distribution modeling in Sumatra by cauchy cluster process: comparing log-linear and log-additive intensity models
KLL dan Log-Tambahan, TY SUSANTO… - Sains Malaysiana, 2023 - ukm.my
Inhomogeneous cluster point processes have been considered for modeling the distribution
of earthquake epicenters with the spatial trend and clustering patterns. In particular, the …
of earthquake epicenters with the spatial trend and clustering patterns. In particular, the …
Inhomogeneous log-Gaussian Cox processes with piecewise constant covariates: a case study in modeling of COVID-19 transmission risk in East Java
Abstract The inhomogeneous Log-Gaussian Cox Process (LGCP) defines a flexible point
process model for the analysis of spatial point patterns featuring inhomogeneity/spatial trend …
process model for the analysis of spatial point patterns featuring inhomogeneity/spatial trend …
Algorithms for Fitting the Space-Time ETAS Model to Earthquake Catalog Data: A Comparative Study
A Choiruddin, AA Rahman, C Andreas - Journal of Agricultural, Biological …, 2024 - Springer
The space-time epidemic-type aftershock sequence (space-time ETAS) is a standard model
for the analysis of earthquake catalogs. The model considers a semi-parametric conditional …
for the analysis of earthquake catalogs. The model considers a semi-parametric conditional …
Optimizing Neural Network for Parameter Estimation of Highly Multivariate Log Gaussian Cox Process Using Dropout Training
ERF Sakti, A Choiruddin… - 2024 ASU International …, 2024 - ieeexplore.ieee.org
Analyzing highly multivariate spatio-temporal point pattern data is very challenging,
especially using the standard procedure since it cannot handle huge data volume, complex …
especially using the standard procedure since it cannot handle huge data volume, complex …
Earthquake Hazard Modeling in Java Using Space Time Epidemic Type Aftershock Sequence
DT Aprillia, A Choiruddin - 2023 IEEE Asia-Pacific Conference …, 2023 - ieeexplore.ieee.org
Appropriate earthquake hazard modeling is important for Indonesia to produce a more
accurate earthquake hazard map because Indonesia is one of the most vulnerable countries …
accurate earthquake hazard map because Indonesia is one of the most vulnerable countries …
[PDF][PDF] Estimasi Parameter pada Model Highly Multivariate Spatio-temporal Log Gaussian Cox Process menggunakan Probabilistic Deep Learning
ERF Sakti - 2024 - repository.its.ac.id
Data multivariate spatio-temporal point pattern semakin mudah dijumpai akhir-akhir ini
karena pesatnya perkembangan teknologi dalam pengambilan data, seperti lokasi banyak …
karena pesatnya perkembangan teknologi dalam pengambilan data, seperti lokasi banyak …
Species Distribution Modeling with Spatial Point Process: Comparing Poisson and Zero Inflated Poisson-Based Algorithms
J Pratama, A Choiruddin - … Conference on Data Science and Its …, 2022 - ieeexplore.ieee.org
Spatial point pattern is randomly arranged collection of points distributed over space, such
as the locations of a tree species in a forest. Such a study is also commonly known as …
as the locations of a tree species in a forest. Such a study is also commonly known as …
Variable selection for inhomogeneous spatio-temporal Poisson point processes
Spatio-temporal point pattern data are becoming prevalent in many scientific disciplines. We
model the first-order intensity of spatio-temporal point pattern data, considering the intensity …
model the first-order intensity of spatio-temporal point pattern data, considering the intensity …