P-min-Stable Regression Models for Time Series With Extreme Values of Limited Range

IF 1.5 3区环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES

Environmetrics Pub Date : 2025-01-31 DOI:10.1002/env.2897

Leonardo Brandao Freitas Nascimento, Max Sousa Lima, Luiz H. Duczmal

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Abstract

In this paper, a P-min-stable regression model is proposed for a time series of extreme values observed in a limited interval. The model may be useful when the variable or indicator of interest is the minimum value of a series restricted to the unit interval and is related to other variables through a regression structure. The serial extremal dependence is induced through the marginalization of the Kumaraswamy distribution conditioned on a latent $α$ -stable process. The model is flexible to capture trends, seasonality, and non-stationarity. Some properties of the model are presented, as well as the extremogram of the series. Procedures for estimation and inference are discussed and implemented via an Expectation-Maximization algorithm. As an illustration, the model was used to analyze the minimum relative humidity observed in the Brazilian Amazon.

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来源期刊

Environmetrics 环境科学-环境科学

CiteScore

2.90

自引率

17.60%

发文量

审稿时长

18-36 weeks

期刊介绍： Environmetrics, the official journal of The International Environmetrics Society (TIES), an Association of the International Statistical Institute, is devoted to the dissemination of high-quality quantitative research in the environmental sciences. The journal welcomes pertinent and innovative submissions from quantitative disciplines developing new statistical and mathematical techniques, methods, and theories that solve modern environmental problems. Articles must proffer substantive, new statistical or mathematical advances to answer important scientific questions in the environmental sciences, or must develop novel or enhanced statistical methodology with clear applications to environmental science. New methods should be illustrated with recent environmental data.