Some recent developments in statistics for spatial point patterns
J Møller, R Waagepetersen - Annual Review of Statistics and Its …, 2017 - annualreviews.org
This article reviews developments in statistics for spatial point processes obtained within
roughly the past decade. These developments include new classes of spatial point process …
roughly the past decade. These developments include new classes of spatial point process …
Careful prior specification avoids incautious inference for log-Gaussian Cox point processes
SH S⊘ rbye, JB Illian, DP Simpson… - Journal of the Royal …, 2019 - academic.oup.com
Hyperprior specifications for random fields in spatial point process modelling can have a
major influence on the results. In fitting log-Gaussian Cox processes to rainforest tree …
major influence on the results. In fitting log-Gaussian Cox processes to rainforest tree …
[HTML][HTML] A nonparametric penalized likelihood approach to density estimation of space-time point patterns
In this work, we consider space-time point processes and study their continuous space-time
evolution. We propose an innovative nonparametric methodology to estimate the unknown …
evolution. We propose an innovative nonparametric methodology to estimate the unknown …
Regularized estimation for highly multivariate log Gaussian Cox processes
Statistical inference for highly multivariate point pattern data is challenging due to complex
models with large numbers of parameters. In this paper, we develop numerically stable and …
models with large numbers of parameters. In this paper, we develop numerically stable and …
Assessing similarities between spatial point patterns with a Siamese neural network discriminant model
A Jalilian, J Mateu - Advances in Data Analysis and Classification, 2023 - Springer
Identifying structural differences among observed point patterns from several populations is
of interest in several applications. We use deep convolutional neural networks and employ a …
of interest in several applications. We use deep convolutional neural networks and employ a …
Spatial pattern analysis of Haloxylon ammodendron using UAV imagery-A case study in the Gurbantunggut Desert
J Xu, H Gu, Q Meng, J Cheng, Y Liu, J Sheng… - International Journal of …, 2019 - Elsevier
Spatial patterns are not only the foundation for the understanding of plant interactions, but
also reflect the spatial processes among plant populations. The primary requirement of …
also reflect the spatial processes among plant populations. The primary requirement of …
宁夏珍稀濒危植物半日花种群结构和点格局分析.
闫秀, 窦建德, 黄维, 黄文广… - Yingyong Shengtai …, 2020 - search.ebscohost.com
摘要半日花是国家二级珍稀濒危植物, 其种群数量日益减少, 分布区破碎化.
以宁夏新记录物种半日花为研究对象, 分析在沙地和砾石质两种生境下半日花种群结构 …
以宁夏新记录物种半日花为研究对象, 分析在沙地和砾石质两种生境下半日花种群结构 …
Detecting multivariate interactions in spatial point patterns with Gibbs models and variable selection
We propose a method for detecting significant interactions in very large multivariate spatial
point patterns. This methodology thus develops high dimensional data understanding in the …
point patterns. This methodology thus develops high dimensional data understanding in the …
Poisson and logistic regressions for inhomogeneous multivariate point processes: a case study in the Barro Colorado Island plot
A Husain, A Choiruddin - Soft Computing in Data Science: 6th …, 2021 - Springer
This study aims to extend the estimating equations based on the Poisson and logistic
regression likelihoods to model the intensity of a multivariate point process. The proposed …
regression likelihoods to model the intensity of a multivariate point process. The proposed …
A vector of point processes for modeling interactions between and within species using capture‐recapture data
A Diana, E Matechou, JE Griffin, Y Jhala… - …, 2022 - Wiley Online Library
Capture‐recapture (CR) data and corresponding models have been used extensively to
estimate the size of wildlife populations when detection probability is less than 1. When the …
estimate the size of wildlife populations when detection probability is less than 1. When the …