Path integral method for limiting distribution of an estimator arising from an ar(1)-process with a unit root

Shih Feng Huang; Yuh Jia Lee; Hsin Hung Shih

doi:10.1142/S021902571350029X

Path integral method for limiting distribution of an estimator arising from an ar(1)-process with a unit root

Shih Feng Huang, Yuh Jia Lee, Hsin Hung Shih

Graduate Institute of Statistics

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

Abstract

We propose the path-integral technique to derive the characteristic function of the limiting distribution of the unit root test in a first order autoregressive model. Our results provide a new and useful approach to obtain the closed form of the characteristic function of a random variable associated with the limiting distribution, which is realized as a ratio of Brownian functionals on the classical Wiener space.

Original language	English
Article number	1350029
Journal	Infinite Dimensional Analysis, Quantum Probability and Related Topics
Volume	16
Issue number	4
DOIs	https://doi.org/10.1142/S021902571350029X
State	Published - Dec 2013

Keywords

Classical Wiener space
path-integral method
unit root test

Access to Document

10.1142/S021902571350029X

Cite this

@article{7f5e356cad164a87b8a37cd9707fc05e,

title = "Path integral method for limiting distribution of an estimator arising from an ar(1)-process with a unit root",

abstract = "We propose the path-integral technique to derive the characteristic function of the limiting distribution of the unit root test in a first order autoregressive model. Our results provide a new and useful approach to obtain the closed form of the characteristic function of a random variable associated with the limiting distribution, which is realized as a ratio of Brownian functionals on the classical Wiener space.",

keywords = "Classical Wiener space, path-integral method, unit root test",

author = "Huang, {Shih Feng} and Lee, {Yuh Jia} and Shih, {Hsin Hung}",

note = "Funding Information: ∗Research supported by the National Science Council of Taiwan.",

year = "2013",

month = dec,

doi = "10.1142/S021902571350029X",

language = "???core.languages.en_GB???",

volume = "16",

journal = "Infinite Dimensional Analysis, Quantum Probability and Related Topics",

issn = "0219-0257",

number = "4",

}

TY - JOUR

T1 - Path integral method for limiting distribution of an estimator arising from an ar(1)-process with a unit root

AU - Huang, Shih Feng

AU - Lee, Yuh Jia

AU - Shih, Hsin Hung

N1 - Funding Information: ∗Research supported by the National Science Council of Taiwan.

PY - 2013/12

Y1 - 2013/12

N2 - We propose the path-integral technique to derive the characteristic function of the limiting distribution of the unit root test in a first order autoregressive model. Our results provide a new and useful approach to obtain the closed form of the characteristic function of a random variable associated with the limiting distribution, which is realized as a ratio of Brownian functionals on the classical Wiener space.

AB - We propose the path-integral technique to derive the characteristic function of the limiting distribution of the unit root test in a first order autoregressive model. Our results provide a new and useful approach to obtain the closed form of the characteristic function of a random variable associated with the limiting distribution, which is realized as a ratio of Brownian functionals on the classical Wiener space.

KW - Classical Wiener space

KW - path-integral method

KW - unit root test

UR - http://www.scopus.com/inward/record.url?scp=84890362306&partnerID=8YFLogxK

U2 - 10.1142/S021902571350029X

DO - 10.1142/S021902571350029X

M3 - 期刊論文

AN - SCOPUS:84890362306

SN - 0219-0257

VL - 16

JO - Infinite Dimensional Analysis, Quantum Probability and Related Topics

JF - Infinite Dimensional Analysis, Quantum Probability and Related Topics

IS - 4

M1 - 1350029

ER -

Path integral method for limiting distribution of an estimator arising from an ar(1)-process with a unit root

Abstract

Keywords

Access to Document

Fingerprint

Cite this