Estimating the order of sinusoidal models using the adaptively penalized likelihood approach: large sample consistency properties

Khushboo Surana; Sharmistha Mitra; Amit Mitra; Petre Stoica

doi:10.1016/j.sigpro.2016.04.001

Estimating the order of sinusoidal models using the adaptively penalized likelihood approach: large sample consistency properties

Khushboo Surana, Sharmistha Mitra, Amit Mitra, Petre Stoica

Economics

Research output: Contribution to journal › Article › peer-review

Abstract

Recently, the paper [2] introduced a method for model order estimation based on penalizing adaptively the likelihood (PAL). In this paper, we use the PAL based order estimation method for a nonlinear sinusoidal model and study its asymptotic statistical properties. We prove that the estimator of the model order using the PAL rule is consistent. Simulation examples are presented to illustrate the performance of the PAL method for small sample sizes and to compare it with that of three information criterion-based methods.

Original language	English
Pages (from-to)	204-211
Number of pages	8
Journal	Signal processing
Volume	128
Early online date	6 Apr 2016
DOIs	https://doi.org/10.1016/j.sigpro.2016.04.001
Publication status	Published - Nov 2016

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10.1016/j.sigpro.2016.04.001

https://www.sciencedirect.com/science/article/abs/pii/S0165168416300238?via%3Dihub

Cite this

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title = "Estimating the order of sinusoidal models using the adaptively penalized likelihood approach: large sample consistency properties",

abstract = "Recently, the paper [2] introduced a method for model order estimation based on penalizing adaptively the likelihood (PAL). In this paper, we use the PAL based order estimation method for a nonlinear sinusoidal model and study its asymptotic statistical properties. We prove that the estimator of the model order using the PAL rule is consistent. Simulation examples are presented to illustrate the performance of the PAL method for small sample sizes and to compare it with that of three information criterion-based methods.",

author = "Khushboo Surana and Sharmistha Mitra and Amit Mitra and Petre Stoica",

year = "2016",

month = nov,

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AU - Surana, Khushboo

AU - Mitra, Sharmistha

AU - Mitra, Amit

AU - Stoica, Petre

PY - 2016/11

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AB - Recently, the paper [2] introduced a method for model order estimation based on penalizing adaptively the likelihood (PAL). In this paper, we use the PAL based order estimation method for a nonlinear sinusoidal model and study its asymptotic statistical properties. We prove that the estimator of the model order using the PAL rule is consistent. Simulation examples are presented to illustrate the performance of the PAL method for small sample sizes and to compare it with that of three information criterion-based methods.

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DO - 10.1016/j.sigpro.2016.04.001

M3 - Article

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EP - 211

JO - Signal processing

JF - Signal processing

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