Title:
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A zero-inflated geometric INAR(1) process with random coefficient (English) |
Author:
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Bakouch, Hassan S. |
Author:
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Mohammadpour, Mehrnaz |
Author:
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Shirozhan, Masumeh |
Language:
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English |
Journal:
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Applications of Mathematics |
ISSN:
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0862-7940 (print) |
ISSN:
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1572-9109 (online) |
Volume:
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63 |
Issue:
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1 |
Year:
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2018 |
Pages:
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79-105 |
Summary lang:
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English |
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Category:
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math |
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Summary:
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Many real-life count data are frequently characterized by overdispersion, excess zeros and autocorrelation. Zero-inflated count time series models can provide a powerful procedure to model this type of data. In this paper, we introduce a new stationary first-order integer-valued autoregressive process with random coefficient and zero-inflated geometric marginal distribution, named ZIGINAR$_{\rm RC}(1)$ process, which contains some sub-models as special cases. Several properties of the process are established. Estimators of the model parameters are obtained and their performance is checked by a small Monte Carlo simulation. Also, the behavior of the inflation parameter of the model is justified. We investigate an application of the process using a real count climate data set with excessive zeros for the number of tornados deaths and illustrate the best performance of the proposed process as compared with a set of competitive INAR(1) models via some goodness-of-fit statistics. Consequently, forecasting for the data is discussed with estimation of the transition probability and expected run length at state zero. Moreover, for the considered data, a test of the random coefficient for the proposed process is investigated. (English) |
Keyword:
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randomized binomial thinning |
Keyword:
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geometric minima |
Keyword:
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estimation |
Keyword:
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likelihood ratio test |
Keyword:
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mixture distribution |
Keyword:
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realization with random size |
MSC:
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62M10 |
idZBL:
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Zbl 06861543 |
idMR:
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MR3763983 |
DOI:
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10.21136/AM.2018.0082-17 |
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Date available:
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2018-03-13T06:25:46Z |
Last updated:
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2020-07-06 |
Stable URL:
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http://hdl.handle.net/10338.dmlcz/147115 |
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Reference:
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