70 citations · 139 across the 22 of their papers we have counts for
12 papers · 1 filter
GARTFIMA Models: A Class of Observation-Driven Models with Tempered Fractional Dynamics
Guilherme Pumi, Sharandeep Singh Pandher, Taiane Schaedler Prass
This paper introduces a class of observation-driven models whose systematic component includes a tempered fractional differencing term. This specification generalizes long-range de…
Bayes Estimation of GLARMA Models With Applications
Guilherme Pumi, Ana Julia Alves Câmara
This work presents a Bayesian approach for parameter estimation in the class of Generalized Linear Autoregressive Moving Average (GLARMA) models, extending the methodology beyond t…
A Novel Multiple Imputation Approach For Parameter Estimation in Observation-Driven Time Series Models With Missing Data
Guilherme Pumi, Taiane Schaedler Prass, Douglas Krauthein Verdum
Handling missing data in time series is a complex problem due to the presence of temporal dependence. General-purpose imputation methods, while widely used, often distort key stati…
PRTree: An R Package for Probabilistic Regression Trees with Built-in Missing Data Handling
Taiane Schaedler Prass, Alisson Silva Neimaier, Guilherme Pumi
PRTree is an R package for fitting Probabilistic Regression Trees (PRTrees), a class of regression trees that replaces deterministic splits with probabilistic associations to produ…
A Matsuoka-Based GARMA Model for Hydrological Forecasting: Theory, Estimation, and Applications
Guilherme Pumi, Danilo Hiroshi Matsuoka, Taiane Schaedler Prass +1
Time series in natural sciences, such as hydrology and climatology, and other environmental applications, often consist of continuous observations constrained to the unit interval…
Order selection in GARMA models for count time series: a Bayesian perspective
Katerine Zuniga Lastra, Guilherme Pumi, Taiane Schaedler Prass
Estimation in GARMA models has traditionally been carried out under the frequentist approach. To date, Bayesian approaches for such estimation have been relatively limited. In the…
A two-step approach to production frontier estimation and the Matsuoka's distribution
Danilo Hiroshi Matsuoka, Guilherme Pumi, Hudson da Silva Torrent +1
In this work, we introduce a deterministic frontier model in which efficiency is governed by the Matsuoka distribution, a parsimonious one-parameter specification on design…
Bayesian Analysis of Beta Autoregressive Moving Average Models
Aline Foerster Grande, Guilherme Pumi, Gabriela Bettella Cybis
This work presents a Bayesian approach for the estimation of Beta Autoregressive Moving Average (ARMA) models. We discuss standard choice for the prior distributions and employ…
Estimation of Long-Range Dependent Models with Missing Data: to Impute or not to Impute?
Guilherme Pumi, Gladys Choque Ulloa, Taiane Schaedler Prass
Among the most important models for long-range dependent time series is the class of ARFIMA (Autoregressive Fractionally Integrated Moving Average) models. Estimating the…
Positive Time Series Regression Models
Taiane Schaedler Prass, Jonas Hendler Carlos, Cleiton Guolo Taufemback +1
In this paper we discuss dynamic ARMA-type regression models for time series taking values in . In the proposed model, the conditional mean is modeled by a dynamic stru…
Beta Autoregressive Fractionally Integrated Moving Average Models
Guilherme Pumi, Marcio Valk, Cleber Bisognin +2
In this work we introduce the class of beta autoregressive fractionally integrated moving average models for continuous random variables taking values in the continuous unit interv…
Kumaraswamy autoregressive moving average models for double bounded environmental data
Fábio Mariano Bayer, Débora Missio Bayer, Guilherme Pumi
In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded inte…