Spatial-temporal analysis of cerebral infarction mortality in Hokkaido, Japan: an ecological study using a conditional autoregressive model. [PDF]
Int J Health Geogr, 2022 Ohashi K +9 more
europepmc +1 more source
Seasonal Decomposition‐Enhanced Deep Learning Architecture for Probabilistic Forecasting
Journal of Forecasting, EarlyView.ABSTRACT Time series decomposition as a general preprocessing method has been widely used in the field of time series forecasting. However, since the future is unknown, this preprocessing practice is limited in realistic forecasting, especially in real‐time forecasting scenarios.
Keyan Jin +1 more
wiley +1 more source
A network autoregressive model with GARCH effects and its applications. [PDF]
PLoS One, 2021 Huang SF, Chiang HH, Lin YJ.
europepmc +1 more source
A Bayesian approach for the estimation of weight matrices in spatial autoregressive models [PDF]
, 2022 Tamás Krisztin, Philipp Piribauer
openalex +1 more source
When Are Statistical Forecast Gains Economically Relevant? Evidence From Bitcoin Returns
Journal of Forecasting, EarlyView.ABSTRACT We study how statistical forecast gains for Bitcoin translate into trading profits. Using real‐time out‐of‐sample forecasts from daily bivariate VARs from October 2021 to February 2024, we show that Bitcoin returns are forecastable and that seven predictive indices yield significant gains in directional accuracy (DA).
Rehan Arain, Stephen Snudden
wiley +1 more source
Comparison of Conventional Modeling Techniques with the Neural Network Autoregressive Model (NNAR): Application to COVID-19 Data. [PDF]
J Healthc Eng, 2022 Daniyal M +3 more
europepmc +1 more source
Robust estimation for zero-inflated poisson autoregressive models based on density power divergence
, 2017 Byungsoo Kim, Sangyeol Lee
openalex +2 more sources
Mortality Forecasting Using Variational Inference
Journal of Forecasting, EarlyView.ABSTRACT This paper considers the problem of forecasting mortality rates. A large number of models have already been proposed for this task, but they generally have the disadvantage of either estimating the model in a two‐step process, possibly losing efficiency, or relying on methods that are cumbersome for the practitioner to use.
Patrik Andersson, Mathias Lindholm
wiley +1 more source
The association between climate variables and tuberculosis in Kolaka District, Southeast Sulawesi Province, Indonesia, 2013-2020: a Bayesian autoregressive model. [PDF]
F1000Res, 2023 Tosepu R, Sani A, Effendy DS, Ahmad OAI.
europepmc +1 more source