Results 161 to 170 of about 56,489 (266)

Hybrid framework for on‐the‐fly diagnosis of energy inefficiency in multi‐unit processes based on data‐driven and knowledge‐based integration

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Pinpointing the true roots of energy waste in large, multi‐unit industrial systems is notoriously difficult: the data are high‐dimensional, and process units are tightly interlinked. This paper presents a powerful hybrid diagnostic framework that integrates explainable AI (XAI), Granger causality (GC), and fault tree analysis (FTA).
Mohamed El Koujok, Hakim Ghezzaz, Mouloud Amazouz   +2 more
wiley   +1 more source

Maximum likelihood estimation of matrix exponential spatial specification on seemingly unrelated regression-spatial autoregressive model. [PDF]

MethodsX
Marsono, Setiawan, Kuswanto H.
europepmc   +1 more source

Improved prediction of new COVID-19 cases using a simple vector autoregressive model: evidence from seven New York state counties. [PDF]

Biol Methods Protoc, 2023
Kitaoka T, Takahashi H.
europepmc   +1 more source

Modified F‐tests for assessing tree radial growth under linear‐circular regression models with correlated errors: A comprehensive toolbox rooted in G. E. P. Box's theorems

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, Tomoaki Imoto, Kunio Shimizu   +2 more
wiley   +1 more source

Bayesian modeling of the effect of vaccination and the delta and omicron variants on the COVID-19 epidemic in Burkina Faso using poisson log-linear autoregressive model. [PDF]

Front Public Health
Somda SMA, Traore I, Dabone BEA.
europepmc   +1 more source

A first-order binomial-mixed Poisson integer-valued autoregressive model with serially dependent innovations. [PDF]

J Appl Stat, 2023
Chen Z, Dassios A, Tzougas G.
europepmc   +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

A non-linear integer-valued autoregressive model with zero-inflated data series. [PDF]

J Appl Stat
Popović PM, Bakouch HS, Ristić MM.
europepmc   +1 more source

Sparse maximum likelihood estimation of regression models

Canadian Journal of Statistics, EarlyView.
Abstract For regression model selection and estimation, we study a small set of candidate models of maximum likelihood from which all information criteria such as the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) choose their models.
Min Tsao
wiley   +1 more source

On the Bayesian generalized extreme value mixture autoregressive model with adjusted SNR in non-standard actuarial data. [PDF]

MethodsX
Lande CR, Iriawan N, Prastyo DD.
europepmc   +1 more source