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Related papers: Full Open Population Capture-Recapture Models with…

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The composite likelihood (CL) is amongst the computational methods used for estimation of the generalized linear mixed model (GLMM) in the context of bivariate meta-analysis of diagnostic test accuracy studies. Its advantage is that the…

Methodology · Statistics 2018-07-12 Aristidis K. Nikoloulopoulos

This paper provides further insight into the key concept of missing at random (MAR) in incomplete data analysis. Following the usual selection modelling approach we envisage two models with separable parameters: a model for the response of…

Statistics Theory · Mathematics 2007-06-13 Guobing Lu , John B. Copas

Accurate predictions of when a component will fail are crucial when planning maintenance, and by modeling the distribution of these failure times, survival models have shown to be particularly useful in this context. The presented…

Machine Learning · Computer Science 2024-03-28 Olov Holmer , Mattias Krysander , Erik Frisk

Obtaining reliable and precise estimates of wildlife species abundance and distribution is essential for the conservation and management of animal populations and natural reserves. Spatial capture-recapture (SCR) models provide estimates of…

The composite likelihood (CL) is amongst the computational methods used for the estimation of high-dimensional multivariate normal (MVN) copula models with discrete responses. Its computational advantage, as a surrogate likelihood method,…

Methodology · Statistics 2022-03-10 Aristidis K. Nikoloulopoulos

In situations where both extreme and non-extreme data are of interest, modelling the whole data set accurately is important. In a univariate framework, modelling the bulk and tail of a distribution has been extensively studied before.…

Methodology · Statistics 2023-10-11 Lídia M. André , Jennifer L. Wadsworth , Adrian O'Hagan

Relative abundance, measured as the number of animals caught per unit of sampling effort (CPUE), is commonly used to monitor fish and wildlife populations, largely because sampling methods are cost-effective to implement. Modeling relative…

Applications · Statistics 2026-05-12 Kevin M. Collins , Erin M. Schliep , Tyler Wagner , Christopher K. Wikle

In this paper, we consider capture-recapture experiments with heterogenous catchability. In the setting we consider, the widespread Huggins-Alho estimator is not very suitable and we introduce and study a new generalized Horvitz-Thompson…

Applications · Statistics 2011-11-09 Yakir Berchenko , Richard G. White , Cyprian Wejnert , Simon D. W. Frost

1. Joint species distribution models (JSDMs) have gained considerable traction among ecologists over the past decade, due to their capacity to answer a wide range of questions at both the species- and the community-level. The family of…

Methodology · Statistics 2024-03-19 Pekka Korhonen , Francis K. C. Hui , Jenni Niku , Sara Taskinen , Bert van der Veen

Compartmental epidemic models are among the most popular ones in epidemiology. For the parameters (e.g., the transmission rate) characterizing these models, the majority of researchers simplify them as constants, while some others manage to…

Machine Learning · Statistics 2020-06-02 Wenjie Zheng

In biomedical studies, paired survival data arise naturally when two event times are observed within the same subject. Existing statistical models seldom accommodate both cure fractions and complex dependence structures. In this paper, we…

Methodology · Statistics 2026-04-28 Masaki Hino , Shogo Kato , Takeshi Emura

The missing data problem has been broadly studied in the last few decades and has various applications in different areas such as statistics or bioinformatics. Even though many methods have been developed to tackle this challenge, most of…

Machine Learning · Statistics 2021-06-10 Thu Nguyen , Khoi Minh Nguyen-Duy , Duy Ho Minh Nguyen , Binh T. Nguyen , Bruce Alan Wade

Inherent differences in behaviour of individual animal movement can introduce bias into estimates of population parameters derived from mark-recapture data. Additionally, quantifying individual heterogeneity is of considerable interest in…

Applications · Statistics 2015-11-24 Jessica H Ford , Toby A Patterson , Mark V Bravington

Estimation of population size using incomplete lists (also called the capture-recapture problem) has a long history across many biological and social sciences. For example, human rights and other groups often construct partial and…

Methodology · Statistics 2021-08-03 Manjari Das , Edward H. Kennedy , Nicholas P. Jewell

Efficient estimation of population size from dependent dual-record system (DRS) remains a statistical challenge in capture-recapture type experiment. Owing to the nonidentifiability of the suitable Time-Behavioral Response Variation model…

Methodology · Statistics 2020-08-10 Kiranmoy Chatterjee , Diganta Mukherjee

Multivariate time-dependent data, where multiple features are observed over time for a set of individuals, are increasingly widespread in many application domains. To model these data we need to account for relations among both time…

Methodology · Statistics 2021-04-08 Alessandro Casa , Charles Bouveyron , Elena Erosheva , Giovanna Menardi

Multi-state capture-recapture data comprise individual-specific sighting histories together with information on individuals' states related, for example, to breeding status, infection level, or geographical location. Such data are often…

Applications · Statistics 2023-11-16 Sina Mews , Roland Langrock , Ruth King , Nicola Quick

Capture-recapture experiments are widely used to estimate the abundance of a finite population. Based on capture-recapture data, the empirical likelihood (EL) method has been shown to outperform the conventional conditional likelihood (CL)…

Methodology · Statistics 2025-07-15 Yang Liu , Pengfei Li , Yukun Liu

Several approaches have been proposed in the literature for clustering multivariate ordinal data. These methods typically treat missing values as absent information, rather than recognizing them as valuable for profiling population…

Methodology · Statistics 2024-11-05 Alice Giampino , Antonio Canale , Bernardo Nipoti

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in…

Applications · Statistics 2014-05-06 Rafael Pimentel Maia , Per Madsen , Rodrigo Labouriau