Sử dụng mô hình Poisson không đồng nhất với tính không đẳng hướng không gian và các điểm thay đổi để nghiên cứu dữ liệu ô nhiễm không khí

Environmental and Ecological Statistics - Tập 26 - Trang 153-184 - 2019
Eliane R. Rodrigues1, Geoff Nicholls2, Mario H. Tarumoto3, Guadalupe Tzintzun4
1Instituto de Matemáticas, Universidad Nacional Autónoma de México, Mexico City, Mexico
2Department of Statistics, University of Oxford, Oxford, UK
3Departamento de Estatística, Faculdade de Ciências e Tecnologia, Universidade Estadual Paulista “Júlio de Mesquita Filho”, Presidente Prudente - SP, Brazil
4Instituto Nacional de Ecología y Cambio Climático, Mexico City, Mexico

Tóm tắt

Một quá trình Poisson không đồng nhất được sử dụng để nghiên cứu tỷ lệ mà nồng độ của một chất ô nhiễm vượt qua một ngưỡng nhất định. Một mô hình không đẳng hướng không gian được áp đặt lên các tham số của hàm cường độ Poisson. Đóng góp chính ở đây là cho phép sự hiện diện của các điểm thay đổi theo thời gian, vì dữ liệu có thể có hành vi khác nhau trong các khoảng thời gian khác nhau trong một khoảng thời gian quan sát nhất định. Thêm vào đó, tính không đẳng hướng không gian cũng được áp đặt lên vector của các điểm thay đổi nhằm tính đến sự tương quan có thể giữa các vị trí khác nhau. Việc ước lượng các tham số của mô hình được thực hiện bằng phương pháp suy diễn Bayes thông qua các thuật toán chuỗi Markov Monte Carlo, đặc biệt là lấy mẫu Gibbs và Metropolis-Hastings. Các phiên bản khác nhau của mô hình được áp dụng cho dữ liệu ôzôn từ mạng lưới giám sát của Thành phố Mexico, Mexico. Một phân tích về các kết quả thu được cũng được đưa ra.

Từ khóa

#mô hình Poisson không đồng nhất #điểm thay đổi #tính không đẳng hướng không gian #ô nhiễm không khí #suy diễn Bayes

Tài liệu tham khảo

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