10 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…
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…
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…
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…