In this paper, we introduce the inflated beta autoregressive moving average (I β ARMA)
models for modeling and forecasting time series data that assume values in the intervals (0 …

This paper defines the unit Burr XII autoregressive moving average (UBXII-ARMA) model for
continuous random variables in the unit interval, where any quantile can be modeled by a …

Abstract Two-dimensional (2-D) autoregressive moving average (ARMA) models are
commonly applied to describe real-world image data, usually assuming Gaussian or …

This study proposes a zero-inflated Rayleigh seasonal autoregressive moving average
model with exogenous regressors (iRSARMAX) to model and forecast non-negative time …

This paper introduces a novel approach for dense antenna arrays, which integrates
beamforming and antenna selection. The proposed method aims to optimize the number of …

The method of electromagnetic signal modulation recognition based on wavelet transform
convolutional neural network is studied to improve the effect of electromagnetic signal …

In this paper, we propose an alternative distribution to model count data exhibiting
uni/bimodality. It arises as a weighted version of the beta-binomial distribution, which is …

In this article, we propose five prediction intervals for the beta autoregressive moving
average model. This model is suitable for modeling and forecasting variables that assume …

With the development of artificial intelligence, neural networks have been successfully
applied to the research and analysis of time series data. Considering the dynamic and …

Neste trabalho, propomos o modelo Kumaraswamy inflacionado autorregressivo e de
médias móveis (IKARMA), uma classe de modelos dinâmicos para séries temporais que …