Results 51 to 60 of about 2,396 (180)
Advances in causal discovery methods for ecological time series
Biological Reviews, EarlyView.ABSTRACT Recent advances in data collection technologies (e.g. automated sensor networks, satellite remote sensing, and high‐throughput sequencing) have greatly expanded the availability of ecological time series, enabling new opportunities for causal analyses in dynamic ecosystems.
Kenta Suzuki +6 more
wiley +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT Global imperatives, such as climate change, environmental concerns, and carbon emissions, make green transformation an inevitability in the logistics sector. Green logistics strategy formulation is an economic choice problem, but it also turns out to be a multicriteria decision‐making (MCDM) process that encompasses the triple bottom line (TBL)
Ömer Faruk Görçün +2 more
wiley +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT Institutional investors increasingly rely on ESG ratings to evaluate financially material sustainability risks, while governments promote corporate alignment with the United Nations Sustainable Development Goals (SDGs). Because these frameworks differ substantially in capital market salience and monitoring intensity, board oversight may not ...
Mohamed Hegazy +2 more
wiley +1 more source
Asymptotic properties of cross‐classified sampling designs
Canadian Journal of Statistics, EarlyView.Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley +1 more source
Bayesian inverse ensemble forecasting for COVID‐19
Canadian Journal of Statistics, EarlyView.Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source
Canadian Journal of Statistics, EarlyView.Abstract Annual tree growth is a complex biological process. Modelling radial growth in the trunk by linear‐circular regression with one mode and correlated errors has allowed the definition and assessment of a preferred direction for 1 and 2 years. Here, modified F$$ F $$‐tests are presented for 3 years, 1 mode/year; 1 year, 2 modes for possible main ...
Pierre Dutilleul +2 more
wiley +1 more source
Jackknife bias‐corrected variance estimation for the generalized regression estimator
Canadian Journal of Statistics, EarlyView.Abstract Commonly used variance estimators for the generalized regression estimator (GREG) are based on Taylor linearization and jackknife. Traditionally, a jackknife GREG variance estimator is obtained by jackknifing GREG, which consists of computing GREG from each of several subsamples of the parent sample, and estimating the variance of the parent ...
Marius Stefan, J.N.K Rao
wiley +1 more source
A partial envelope approach for modelling multivariate spatial‐temporal data
Canadian Journal of Statistics, EarlyView.Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja +3 more
wiley +1 more source
Nonlinear permuted Granger causality
Canadian Journal of Statistics, EarlyView.Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley +1 more source
Copula‐based joint modelling of emergency department visits with time‐varying dependence
Canadian Journal of Statistics, EarlyView.Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley +1 more source