Results 161 to 170 of about 62,954 (311)

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

Forecasting New Employment Using Nonrepresentative Online Job Advertisements With an Application to the Italian and EU Labor Market

Journal of Forecasting, EarlyView.
ABSTRACT Using online job advertisement data improves the timeliness and granularity depth of analysis in the labor market in domains not covered by official data. Specifically, its variation over time may be used as an anticipator of official employment variations.
Pietro Giorgio Lovaglio, Mario Mezzanzanica   +1 more
wiley   +1 more source

ARTreeFormer: A faster attention-based autoregressive model for phylogenetic inference. [PDF]

PLoS Comput Biol
Xie T, Mao Y, Zhang C.
europepmc   +1 more source

Spatial Autoregressive Model for Estimation of Visitors' Dynamic Agglomeration Patterns Near Event Location. [PDF]

Sensors (Basel), 2021
Ban T, Usui T, Yamamoto T.
europepmc   +1 more source

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches

Journal of Forecasting, EarlyView.
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann, Mawuli Segnon, Timo Wiedemann   +2 more
wiley   +1 more source

Kinase-substrate prediction using an autoregressive model. [PDF]

Comput Struct Biotechnol J
Esmaili F, Qin Y, Wang D, Xu D.
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

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source

Estimation of parameters and hypothesis testing of multivariate spatial autoregressive model. [PDF]

MethodsX
Sutikno, Purhadi, Fachrunisah, Cahyoko FD.   +3 more
europepmc   +1 more source

Bayesian generalizations of the integer-valued autoregressive model. [PDF]

J Appl Stat, 2022
C Marques F P, Graziadei H, Lopes HF.
europepmc   +1 more source