70 citations · 139 across the 22 of their papers we have counts for
22 papers
Handling Missing Data in Probabilistic Regression Trees
Taiane Schaedler Prass, Alisson Silva Neimaier, Guilherme Pumi
Probabilistic Regression Trees (PRTrees) are a smooth and consistent alternative to classical regression trees, producing continuous predictions through probabilistic split assignm…
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 GARMA Framework for Unit-Bounded Time Series Based on the Unit-Lindley Distribution with Application to Renewable Energy Data
Guilherme Pumi, Danilo Hiroshi Matsuoka, Taiane Schaedler Prass
The Unit-Lindley is a one-parameter family of distributions in obtained from an appropriate transformation of the Lindley distribution. In this work, we introduce a class o…
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…
Mitigating the choice of the duration in DDMS models through a parametric link
Fernando Henrique de Paula e Silva Mendes, Douglas Eduardo Turatti, Guilherme Pumi
One of the most important hyper-parameters in duration-dependent Markov-switching (DDMS) models is the duration of the hidden states. Because there is currently no procedure for es…
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…
Unit-Weibull Autoregressive Moving Average Models
Guilherme Pumi, Taiane Schaedler Prass, Cleiton Guollo Taufemback
In this work we introduce the class of unit-Weibull Autoregressive Moving Average models for continuous random variables taking values in . The proposed model is an observat…
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…
On the behavior of the DFA and DCCA in trend-stationary processes
Taiane Schaedler Prass, Guilherme Pumi
In this work, we develop the asymptotic theory of the Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA) for trend-stationary stochastic processes…
A Dynamic Model for Double Bounded Time Series With Chaotic Driven Conditional Averages
Guilherme Pumi, Taiane Schaedler Prass, Rafael Rigão Souza
In this work we introduce a class of dynamic models for time series taking values on the unit interval. The proposed model follows a generalized linear model approach where the ran…
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…
A Semiparametric Estimator for Long-Range Dependent Multivariate Processes
Guilherme Pumi, Sílvia R. C. Lopes
In this paper we propose a generalization of a class of Gaussian Semiparametric Estimators (GSE) of the fractional differencing parameter for long-range dependent multivariate time…
A Generalization of a Gaussian Semiparametric Estimator on Multivariate Long-Range Dependent Processes
Guilherme Pumi, Sílvia R. C. Lopes
In this paper we propose and study a general class of Gaussian Semiparametric Estimators (GSE) of the fractional differencing parameter in the context of long-range dependent multi…
Parameterization of Copulas and Covariance Decay of Stochastic Processes
Guilherme Pumi, Sílvia R. C. Lopes
In this work we study the problem of constructing stochastic processes with a predetermined covariance decay by parameterizing its marginals and a given family of copulas. We show…
Copulas Related to Manneville-Pomeau Processes
Sílvia R. C. Lopes, Guilherme Pumi
In this work we derive the copulas related to Manneville-Pomeau processes. We examine both bidimensional and multidimensional cases and derive some properties for the related copul…