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Parametric quantile autoregressive moving average models with exogenous terms
Parametric autoregressive moving average models with exogenous terms (ARMAX) have been widely used in the literature. Usually, these models consider...
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Unit-Weibull autoregressive moving average models
In this work we introduce the class of Unit-Weibull Autoregressive Moving Average models for continuous random variables taking values in (0, 1). The...
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Geometric infinitely divisible autoregressive models
In this article, we discuss some geometric infinitely divisible (gid) random variables using the Laplace exponents which are Bernstein functions and...
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Additive partial linear models with autoregressive symmetric errors and its application to the hospitalizations for respiratory diseases
Additive partial linear models with symmetric autoregressive errors of order p are proposed in this paper for modeling time series data....
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Test for conditional quantile change in general conditional heteroscedastic time series models
This study aims to test for detecting a change point in the conditional quantile of general location-scale time series models. This issue is quite...
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Ridge regularization for spatial autoregressive models with multicollinearity issues
This work proposes a new method for building an explanatory spatial autoregressive model in a multicollinearity context. We use Ridge regularization...
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Strong Consistency for the Conditional Self-weighted M Estimator of GRCA(p) Models
In this paper, we investigate the strong consistency for the conditional self-weighted M ( SM , for short) estimator of generalized random coefficient...
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Statistical inference of pth-order generalized binomial autoregressive model
To capture the higher-order autocorrelation structure for finite-range integer-valued time series of counts, and to consider the interdependence...
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Self-exciting hysteretic binomial autoregressive processes
This paper introduces an observation-driven integer-valued time series model, in which the underlying generating stochastic process is binomially...
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Interquantile shrinkage in spatial additive autoregressive models
In this paper, we study the commonness of nonparametric component functions at different quantile levels in spatial additive autoregressive models....
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On bivariate threshold Poisson integer-valued autoregressive processes
To capture the bivariate count time series showing piecewise phenomena, we introduce a first-order bivariate threshold Poisson integer-valued...
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Spatial Autoregressive Models for Circular Data
A class of autoregressive models for spatial circular data is proposed by assuming that samples of angular measurements are drawn from a multivariate...
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A pth-order random coefficients mixed binomial autoregressive process with explanatory variables
To capture the higher-order autocorrelation structure for finite-range integer-valued time series of counts, and to consider the driving effect of...
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Sequential online monitoring for autoregressive time series of counts
This study considers the online monitoring problem for detecting the parameter change in time series of counts. For this task, we construct a...
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On First Order Autoregressive Asymmetric Logistic Process
An additive first order autoregressive model with logistic distribution as marginal is studied. We have obtained a representation of the innovation...
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Bayesian Spatial Modeling of HIV Using Conditional Autoregressive Model
Background: In the spatial analysis, the conventional method for disease modeling and map** is based on a log-linear relationship between relative...
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Estimating weak periodic vector autoregressive time series
This article develops the asymptotic distribution of the least squares estimator of the model parameters in periodic vector autoregressive time...
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Pooled Autoregressive Models for Categorical Data
Time series capture time dependent intra-individual variation within a single participant. When data are collected from more than one subject,...
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Conditional sum of squares estimation of k-factor GARMA models
We analyze issues related to estimation and inference for the constrained sum of squares estimator (CSS) of the k -factor Gegenbauer autoregressive...
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Bayesian analysis of mixture autoregressive models covering the complete parameter space
Mixture autoregressive (MAR) models provide a flexible way to model time series with predictive distributions which depend on the recent history of...
