[HTML][HTML] A review of predictive uncertainty estimation with machine learning
H Tyralis, G Papacharalampous - Artificial Intelligence Review, 2024 - Springer
Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …
distributions, aiming to increase the quantity of information communicated to end users …
A review of probabilistic forecasting and prediction with machine learning
H Tyralis, G Papacharalampous - arXiv preprint arXiv:2209.08307, 2022 - arxiv.org
Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …
distributions, aiming to increase the quantity of information communicated to end users …
tscount: An R package for analysis of count time series following generalized linear models
T Liboschik, K Fokianos, R Fried - Journal of Statistical Software, 2017 - jstatsoft.org
The R package tscount provides likelihood-based estimation methods for analysis and
modeling of count time series following generalized linear models. This is a flexible class of …
modeling of count time series following generalized linear models. This is a flexible class of …
[HTML][HTML] Safety and long-term improvement of mesenchymal stromal cell infusion in critically COVID-19 patients: a randomized clinical trial
CLK Rebelatto, AC Senegaglia, CL Franck… - Stem cell research & …, 2022 - Springer
Background COVID-19 is a multisystem disease that presents acute and persistent
symptoms, the postacute sequelae (PASC). Long-term symptoms may be due to …
symptoms, the postacute sequelae (PASC). Long-term symptoms may be due to …
Quantifying the indirect impact of COVID-19 pandemic on utilisation of outpatient and immunisation services in Kenya: a longitudinal study using interrupted time …
Objective In this study, we assess the indirect impact of COVID-19 on utilisation of
immunisation and outpatient services in Kenya. Design Longitudinal study. Setting Data …
immunisation and outpatient services in Kenya. Design Longitudinal study. Setting Data …
Seasonal variation in the effects of artificial light at night on the occurrence of nocturnally migrating birds in urban areas
FA La Sorte, KG Horton - Environmental Pollution, 2021 - Elsevier
Urban areas often contain large numbers of migratory bird species during seasonal
migration, many of which are nocturnal migrants. How artificial light at night (ALAN) and …
migration, many of which are nocturnal migrants. How artificial light at night (ALAN) and …
Changing environmental conditions underpin long-term patterns of phytoplankton in a freshwater reservoir
Environmental changes can exert strong pressure on freshwater biota and lead to unwanted
alterations of local communities and deterioration of ecosystem services. Disentangling the …
alterations of local communities and deterioration of ecosystem services. Disentangling the …
Multiple response variables regression models in R: The mcglm package
WH Bonat - Journal of Statistical Software, 2018 - jstatsoft.org
This article describes the R package mcglm implemented for fitting multivariate covariance
generalized linear models (McGLMs). McGLMs provide a general statistical modeling …
generalized linear models (McGLMs). McGLMs provide a general statistical modeling …
Seasonal count time series
Count time series are widely encountered in practice. As with continuous valued data, many
count series have seasonal properties. This article uses a recent advance in stationary count …
count series have seasonal properties. This article uses a recent advance in stationary count …
[图书][B] Multiscale geographically weighted regression: Theory and practice
Multiscale geographically weighted regression (MGWR) is an important method that is used
across many disciplines for exploring spatial heterogeneity and modeling local spatial …
across many disciplines for exploring spatial heterogeneity and modeling local spatial …