Results 101 to 110 of about 283,485 (287)
This paper investigates the asymptotic behavior of kernel-based estimators for the error distribution in a first-order autoregressive model with dependent errors. The model assumes that the error terms form an α-mixing sequence with an unknown cumulative
Bing Wang +4 more
doaj +1 more source
ARPILC: An Approach for Short-Term Prediction of Freeway Entrance Flow
In modern intelligent transportation systems, short-term prediction of freeway entrance flow plays an important role in providing travelers timely traffic conditions.
Xiang Wang +5 more
doaj +1 more source
Forecasting industrial production with linear, nonlinear, and structural change models [PDF]
We compare the forecasting performance of linear autoregressive models, autoregressive models with structural breaks, self-exciting threshold autoregressive models, and Markov switching autoregressive models in terms of point, interval, and density ...
Dijk, D.J.C. van, Siliverstovs, B.
core +1 more source
ABSTRACT Emotional and behavioral difficulties (EBD) are common in autistic children, while anxiety and depressive symptoms (ADS) are prevalent in their parents. However, the bidirectional relationship between the parents' and children's symptoms remains unclear, especially in the years following the child's autism diagnosis.
Maëva Monnier +8 more
wiley +1 more source
Analysis of adequacy of autoregressive model for Lithuanian vowels
Autoregressive (AR) model is widely used for modeling of speech signals. Nevertheless, the problem of adequate modelling of Lithuanian speech is still open.
Jonas Kaukėnas +1 more
doaj +1 more source
Model Uncertainty and Bayesian Model Averaging in Vector Autoregressive Processes [PDF]
Economic forecasts and policy decisions are often informed by empirical analysis based on econometric models. However, inference based upon a single model, when several viable models exist, limits its usefulness.
Herman K. van Dijk, Rodney W. Strachan
core
On a Mixture Autoregressive Model
Summary We generalize the Gaussian mixture transition distribution (GMTD) model introduced by Le and co-workers to the mixture autoregressive (MAR) model for the modelling of non-linear time series. The models consist of a mixture of K stationary or non-stationary AR components. The advantages of the MAR model over the GMTD model include
Wong, CS, Li, WK
openaire +2 more sources
Intravenous lanadelumab for the treatment of moderately ill COVID‐19 patients
Aims Kallikrein‐kinin system (KKS) dysregulation is hypothesized to play a pathogenetic role in COVID‐19‐associated pulmonary oedema. To investigate the efficacy and safety of intravenous lanadelumab, a monoclonal antibody that inhibits plasma kallikrein, in COVID‐19, we conducted a phase 2, open‐label, randomized‐controlled, proof‐of‐concept ...
Job J. Engel +12 more
wiley +1 more source
Modelling and Forecasting the Indian Re/US Dollar Exchange Rate [PDF]
This paper develops vector autoregressive and Bayesian vector autoregressive models to forecast the Indian Re/US dollar exchange rate which is governed by a managed floating exchange rate regime. It considers extensions of the monetary model that include
Pami Dua, Rajiv Ranjan
core
ABSTRACT Energy is a fundamental driver of economic growth, shaping productivity, industrialization, and long‐term economic resilience. In sub‐Saharan Africa (SSA), where energy access remains uneven and infrastructure is underdeveloped, understanding sector‐specific energy demand is essential for designing sustainable energy strategies.
Michael Appiah +3 more
wiley +1 more source

