Article
Agriculture, Dairy & Animal Science
Melissa A. Stephen, Chris R. Burke, Jennie E. Pryce, Nicole M. Steele, Peter R. Amer, Susanne Meier, Claire V. C. Phyn, Dorian J. Garrick
Summary: This study compared three methods for deriving phenotypes from incomplete data. The results showed that estimated heritabilities tended to be higher when left censoring was reduced. For sires, using some methods, phenotypes derived from one observation per offspring provided comparable sire rankings to three observations per offspring.
JOURNAL OF ANIMAL SCIENCE AND BIOTECHNOLOGY
(2023)
Article
Agriculture, Dairy & Animal Science
M. A. Stephen, C. R. Burke, N. Steele, J. E. Pryce, S. Meier, P. R. Amer, C. V. C. Phyn, D. J. Garrick
Summary: In this study, the genetic and phenotypic relationships between anogenital distance (AGD) and body stature and fertility traits in dairy cattle were characterized. The results showed that AGD is a moderately heritable trait and is associated with reproductive success in lactating cows.
JOURNAL OF DAIRY SCIENCE
(2023)
Article
Statistics & Probability
Hai-Dang Dau, Nicolas Chopin
Summary: The paper proposes a new waste-free sequential Monte Carlo (SMC) algorithm that utilizes the outputs of all intermediate Markov chain Monte Carlo (MCMC) steps as particles. The consistency and asymptotic normality of its output are established, and insights on estimating the asymptotic variance of any particle estimate are developed. Empirical results show that waste-free SMC tends to outperform standard SMC samplers, particularly in scenarios where the mixing of the considered MCMC kernels decreases across iterations.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
(2022)
Article
Automation & Control Systems
Jianqing Fan, Bai Jiang, Qiang Sun
Summary: This paper establishes Hoeffding's lemma and inequality for bounded functions of general-state space and not necessarily reversible Markov chains, showing the necessity of boundedness of functions for such results. The optimality of the ratio between variance proxies in the Markov-dependent and independent settings is characterized. The new results are applied to various practical problems to showcase their usefulness.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Fabian Joswig, Simon Kuberski, Justus T. Kuhlmann, Jan Neuendorf
Summary: We introduce pyerrors, a Python package for statistical error analysis of Monte Carlo data. It combines linear error propagation using automatic differentiation with the Gamma-method for reliable estimation of autocorrelation times. pyerrors allows for easy combination of data from different sources while preserving the information on the origin of error components. It can be seamlessly integrated into the existing scientific python ecosystem for efficient and compact analyses.
COMPUTER PHYSICS COMMUNICATIONS
(2023)
Article
Soil Science
Siegfried C. K. Hofman, D. J. Brus
Summary: This study utilized a geo-statistical simulation approach to predict the variance of mean NO3-N content in agricultural fields, revealing a large variation in NO3-N variance among the sixteen fields.
Article
Astronomy & Astrophysics
Xia Ding, Xingyou Huang, Haitao Wang, Yanqiu Shen
Summary: The study utilizes the Markov chain Monte Carlo (MCMC) algorithm for retrieving ice cloud microphysical properties, demonstrating that the algorithm performs well in both simulated and observational tests.
EARTH AND SPACE SCIENCE
(2021)
Article
Computer Science, Theory & Methods
Mary Llewellyn, Ruth King, Victor Elvira, Gordon Ross
Summary: This paper presents a novel algorithm for fitting state-space models, using Metropolis-within-Gibbs sampling guided by a deterministic hidden Markov model (HMM). The algorithm can efficiently handle highly correlated latent states and parameters, and is applicable to models that exhibit near-chaotic behavior.
STATISTICS AND COMPUTING
(2023)
Article
Geochemistry & Geophysics
Hai Huang, Jianxi Huang, Yantong Wu, Wen Zhuo, Jianjian Song, Xuecao Li, Li Li, Wei Su, Han Ma, Shunlin Liang
Summary: This study aims to better quantify model uncertainty in a data assimilation system. The proposed Bayesian posterior-based ensemble Kalman filter improves the accuracy of winter wheat yield estimation compared to traditional methods and provides an important reference for similar agricultural landscapes worldwide at the regional scale.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Automation & Control Systems
Xiaonan Li, Ping Ma, Zehua Wu, Tao Chao, Ming Yang
Summary: This paper aims to improve the efficiency of parameter identification of the nonlinear state-space model (SSM). It proposes an efficient algorithm that gradually estimates the unknown parameters in two stages. In the first stage, a reduced region is established, where a local Gaussian Process regression (GPR) and optimum Latin hypercube design (OLHD) are used. In the second stage, the MCMC method is employed to identify the unknown parameters more accurately. The algorithm demonstrates good performance in accuracy and efficiency based on two examples.
IET CONTROL THEORY AND APPLICATIONS
(2023)
Article
Economics
Nianling Wang, Zhusheng Lou
Summary: The stochastic volatility (SV) model is widely used to study time-varying volatility. However, the linearity assumption for transition equation in basic SV model is restrictive. To allow for nonlinearity, we proposed a semiparametric SV model that specifies a nonparametric transition equation for log-volatility using natural cubic splines. The empirical applications to Bitcoin and convertible bond return data indicate that the transition equations of their log-volatility are highly nonlinear. Taking nonlinearity into account, the semi-parametric SV model can improve the likelihood of the basic SV model both in-sample and out-of-sample.
ECONOMIC MODELLING
(2023)
Article
Energy & Fuels
Per Bjarte Solibakke
Summary: This empirical study developed, implemented, and analyzed multifactor stochastic volatility models for the financial Nordic/Baltic power markets, focusing on stochastic volatility projections, forecasts, and market transparency. The models created mean-reverting factors for front year and quarter financial electricity contracts, improving market visibility and facilitating risk management.
Article
Computer Science, Artificial Intelligence
Arpit Kapoor, Eshwar Nukala, Rohitash Chandra
Summary: The major challenge in Bayesian neural networks is to develop effective sampling methods for addressing deep neural networks and big data-related problems. This paper proposes a synergy of neuroevolution and Bayesian neural networks, utilizing particle swarm optimization as efficient proposal distributions in tempered MCMC sampling. The results demonstrate improved prediction accuracy and reduced computational time compared to traditional methods for time-series and pattern classification problems.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Geological
Chao Zhao, Wenping Gong, Tianzheng Li, C. Hsein Juang, Huiming Tang, Hui Wang
Summary: Accurate characterization of subsurface stratigraphic configuration is crucial to geotechnical engineering work, but uncertainty can be significant due to complexity and limited data availability. This paper presents a method for characterizing subsurface stratigraphy with limited borehole data, demonstrating its effectiveness and advantages through comparative analyses and a case study in Western Australia.
ENGINEERING GEOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Muhammad Javvad Ur Rehman, Raheel Zafar, Hammad Dilpazir, Muhammad Farhan Sohail, Muhammad Arslan Khan, Rifat Jahan
Summary: This study examines parameter inference in dynamical systems from the perspective of Bayesian inference. It proposes a sequential embedded estimation technique, called the Augmented Sequential Markov Chain Monte Carlo (ASMCMC) procedure, to estimate posterior density and obtain parameter inference in nonlinear and non-Gaussian dynamical systems.
JOURNAL OF SENSORS
(2022)
Article
Biodiversity Conservation
Teresa Montras-Janer, Jonas Knape, Lovisa Nilsson, Ingunn Tombre, Tomas Part, Johan Mansson
JOURNAL OF APPLIED ECOLOGY
(2019)
Article
Ecology
Mathieu Chevalier, Jonas Knape
Review
Biodiversity Conservation
Jonas Josefsson, Matthew Hiron, Debora Arlt, Alistair G. Auffret, Ake Berg, Mathieu Chevalier, Anders Glimskar, Goran Hartman, Ineta Kacergyte, Julian Klein, Jonas Knape, Ane T. Laugen, Matthew Low, Matthieu Paquet, Marianne Pasanen-Mortensen, Zuzanna M. Rosin, Diana Rubene, Michal Zmihorski, Tomas Part
CONSERVATION LETTERS
(2020)
Article
Agriculture, Multidisciplinary
Teresa Montras-Janer, Jonas Knape, Marianne Stoessel, Lovisa Nilsson, Ingunn Tombre, Tomas Part, Johan Mansson
AGRICULTURE ECOSYSTEMS & ENVIRONMENT
(2020)
Article
Ecology
Matthieu Paquet, Debora Arlt, Jonas Knape, Matthew Low, Par Forslund, Tomas Part
JOURNAL OF ANIMAL ECOLOGY
(2020)
Article
Ecology
Alejandro Ruete, Debora Arlt, Ake Berg, Jonas Knape, Michal Zmihorski, Tomas Part
ECOLOGY AND EVOLUTION
(2020)
Article
Engineering, Environmental
Jonas Knape, Stephen James Coulson, Rene van der Wal, Debora Arlt
Summary: Opportunistic reporting of species observations to online platforms provides valuable information about the distribution and status of organisms in the wild. However, challenges arise when analyzing temporal changes in organisms due to the lack of a clear sampling design and changes in reporting over time.
Article
Biodiversity Conservation
Ineta Kacergyte, Debora Arlt, Ake Berg, Michal Zmihorski, Jonas Knape, Zuzanna M. Rosin, Tomas Part
Summary: The size of wetlands is positively associated with local species richness, pair abundance, and chick abundance. Creating mainly small wetlands with a few larger ones is suggested to benefit breeding wetland bird communities at the regional scale.
BIOLOGICAL CONSERVATION
(2021)
Article
Ecology
Ineta Kacergyte, Erik Petersson, Debora Arlt, Micaela Hellstrom, Jonas Knape, Johan Spens, Michal Zmihorski, Tomas Part
Summary: Wetlands are important for biodiversity and ecosystem services. Human activities have led to global wetland decline, but created wetlands can help counteract this loss. Fish and amphibians coexist in created wetlands, with certain differences in species occurrence and interactions. Additional habitat heterogeneity can enable the coexistence of these taxa.
FRESHWATER BIOLOGY
(2021)
Article
Ecology
Matthieu Paquet, Jonas Knape, Debora Arlt, Par Forslund, Tomas Part, Oystein Flagstad, Carl G. Jones, Malcolm A. C. Nicoll, Ken Norris, Josephine M. Pemberton, Hakan Sand, Linn Svensson, Vikash Tatayah, Petter Wabakken, Camilla Wikenros, Mikael Akesson, Matthew Low
Summary: This study found that integrated population models (IPMs) often overestimate the contribution of immigration to changes in population growth, requiring large sample sizes and high temporal variation to accurately estimate immigration contributions. Using simulated and empirical data, it was shown that distinguishing between accurate estimation and overestimation of immigration contributions in IPMs can be challenging.
METHODS IN ECOLOGY AND EVOLUTION
(2021)
Article
Biodiversity Conservation
Ineta Kacergyte, Tomas Part, Ake Berg, Debora Arlt, Michal Zmihorski, Jonas Knape
Summary: Restoring wetlands is an important conservation tool for improving birds' habitats. However, the effectiveness of such restorations is not well known. A study in Sweden found that island breeding bird populations increased by 62% to 315% following wetland restorations. The responses varied among different bird groups and were associated with large uncertainties.
BIOLOGICAL CONSERVATION
(2022)
Article
Ecology
Christer Solbreck, Jonas Knape, Jonas Forare
Summary: Insect population dynamics are influenced by intrinsic and extrinsic factors, such as density dependence, trophic web interactions, and weather conditions. A study on a natural, low-density insect population revealed that population changes during summer were more predictable compared to the long wintering period.
ECOLOGY AND EVOLUTION
(2022)
Article
Environmental Sciences
Jonas Knape
Summary: Many monitoring programs provide annual indices of relative change in ecological status, but using a single reference year may result in increased uncertainty. However, using the mean of ecological status over several years as the reference period can reduce uncertainty.
ENVIRONMENTAL AND ECOLOGICAL STATISTICS
(2023)
Article
Biodiversity Conservation
Ineta Kacergyte, Jonas Knape, Michal Zmihorski, Debora Arlt, Tomas Part
Summary: Conservation initiatives have been implemented to support declining water-related biodiversity through wetland creation, and multiple studies have evaluated the suitability of created wetlands for birds and amphibians. However, few studies have considered the species associations that might affect the outcome. In this study, using joint species distribution models, the researchers explored the species associations of birds, amphibians, and fish in created biodiversity wetlands in Sweden. The findings suggest potential conservation conflicts between wetland creation for birds and fish, while synergies between wetland creation for birds and amphibians were observed. Further research is needed to consolidate these synergies and investigate amphibian reproductive output in bird-rich wetlands.
BIOLOGICAL CONSERVATION
(2023)
Article
Ecology
Stanislas Rigal, Jonas Knape
Summary: In the face of declining biodiversity, it is crucial to monitor its fate for conservation strategies. While aggregated indices like geometric means can identify at-risk species groups, they mask the variability between species in their temporal trajectories, which is important for conservation actions. To address this, we propose a toolbox that utilizes dynamic factor analysis to investigate the compositions of species dynamics in multi-species indices, enabling a deeper exploration of biodiversity change and informing conservation policies.
METHODS IN ECOLOGY AND EVOLUTION
(2023)