Vectors of proportions arise in a great variety of fields: chemistry, economics, medicine, sociology and many others. Supposing that a whole can be split into D mutually exclusive and exhaustive categories, vectors describing the percentage of each category on the total are referred to as compositional data. This chapter presents a further generalization of the Dirichlet, called double flexible Dirichlet (DFD), that takes advantage of a finite mixture structure similar to that of the FD (depending on D(D + 1)/2 mixture components) and enables positive covariances. Some theoretical results are shown and an estimation procedure based on the EM algorithm is proposed, including an ad hoc initialization strategy. A simulation study aimed at evaluating the performance of the EM algorithm under several parameter configurations is included.

Ascari, R., Migliorati, S., Ongaro, A. (2021). The Double Flexible Dirichlet: A Structured Mixture Model for Compositional Data. In Y. Dimotikalis, A. Karagrigoriou, C. Parpoula, C.H. Skiadas (a cura di), Applied Modeling Techniques and Data Analysis 2 Financial, Demographic, Stochastic and Statistical Models and Methods Volume 8 - Big Data, Artificial Intelligence and Data Analysis (pp. 137-152). Wiley [10.1002/9781119821724.ch10].

The Double Flexible Dirichlet: A Structured Mixture Model for Compositional Data

Ascari, R
;
Migliorati, S;Ongaro, A
2021

Abstract

Vectors of proportions arise in a great variety of fields: chemistry, economics, medicine, sociology and many others. Supposing that a whole can be split into D mutually exclusive and exhaustive categories, vectors describing the percentage of each category on the total are referred to as compositional data. This chapter presents a further generalization of the Dirichlet, called double flexible Dirichlet (DFD), that takes advantage of a finite mixture structure similar to that of the FD (depending on D(D + 1)/2 mixture components) and enables positive covariances. Some theoretical results are shown and an estimation procedure based on the EM algorithm is proposed, including an ad hoc initialization strategy. A simulation study aimed at evaluating the performance of the EM algorithm under several parameter configurations is included.
Capitolo o saggio
Ad hoc initialization strategy; Compositional data; Double flexible Dirichlet; EM algorithm; Estimation procedure;
English
Applied Modeling Techniques and Data Analysis 2 Financial, Demographic, Stochastic and Statistical Models and Methods Volume 8 - Big Data, Artificial Intelligence and Data Analysis
Dimotikalis, Y; Karagrigoriou, A; Parpoula, C; Skiadas, CH
mar-2021
2021
9781786306746
Wiley
137
152
Ascari, R., Migliorati, S., Ongaro, A. (2021). The Double Flexible Dirichlet: A Structured Mixture Model for Compositional Data. In Y. Dimotikalis, A. Karagrigoriou, C. Parpoula, C.H. Skiadas (a cura di), Applied Modeling Techniques and Data Analysis 2 Financial, Demographic, Stochastic and Statistical Models and Methods Volume 8 - Big Data, Artificial Intelligence and Data Analysis (pp. 137-152). Wiley [10.1002/9781119821724.ch10].
none
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/311438
Citazioni
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
Social impact