Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Brendan McCabe"'
Publikováno v:
Entropy, Vol 25, Iss 4, p 549 (2023)
Censored data are frequently found in diverse fields including environmental monitoring, medicine, economics and social sciences. Censoring occurs when observations are available only for a restricted range, e.g., due to a detection limit. Ignoring c
Externí odkaz:
https://doaj.org/article/be53ec675b1e481ba3fc3492354e3b80
Publikováno v:
Journal of the Royal Statistical Society Series C: Applied Statistics. 71:495-516
We consider a low count data INAR (Integer Autoregressive Regression) model in which the arrivals are modelled non-parametrically and are allowed to contain covariates. Accommodating possible covariates is important as exogenous variability, such as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05d65c8d33f8fb35f511424cc3463230
https://doi.org/10.1111/rssc.12543
https://doi.org/10.1111/rssc.12543
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a08c9b6f64ed794ea74f4564a7acf86
https://doi.org/10.2139/ssrn.4098375
https://doi.org/10.2139/ssrn.4098375
Autor:
Brendan McCabe, Yao Rao
Publikováno v:
The Manchester School. 88:211-228
It is well known, in structural break problems, that it is much easier to detect the existence of a break in a data set than to determine the location of such a break in the sample span. This paper investigates why, in the context of Gaussian linear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50094742e0aa84da65c2fa55da56290d
https://doi.org/10.1111/manc.12298
https://doi.org/10.1111/manc.12298
Testing for Structural Breaks – A New Self-Normalization Approach Based on the Adjusted Sample Range
Publikováno v:
SSRN Electronic Journal.
In this paper, we introduce adjusted-range based Kolmogorov-Smirnov (KS) type statistics to test for structural breaks in the mean of a process and also in a more general setting. We propose a normalization based on the adjusted-range of a partial su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed90a959cf9c6be0273bad59cd494c15
https://doi.org/10.2139/ssrn.3850894
https://doi.org/10.2139/ssrn.3850894
Publikováno v:
SSRN Electronic Journal.
This paper proposes an adjusted-range based self-normalized test for change in correlation. Unlike the self-normalization approach proposed by Lobato (2001) and Shao (2010), which relies on the variance of the partial sum process as a self-normalizer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e97fcaf00cec9a4ba92e2d5fe4d9139
https://doi.org/10.2139/ssrn.3881190
https://doi.org/10.2139/ssrn.3881190
Publikováno v:
SSRN Electronic Journal.
This article considers model averaging in the class of the integer-valued autoregressive (INAR) processes. The INAR process is a class of structural models that can be used to model dependent count data in fields such as medicine, economics, finance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d4a0dfe6e8bee68af1a3050a3c725f7
https://doi.org/10.2139/ssrn.3846927
https://doi.org/10.2139/ssrn.3846927
Publikováno v:
Economics Letters. 213:110394
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5d8321287835f022591aca6d22652a9
https://doi.org/10.1016/j.econlet.2022.110394
https://doi.org/10.1016/j.econlet.2022.110394
Autor:
David Harris, Brendan McCabe
Publikováno v:
Econometric Theory. 35:1111-1145
This article considers testing for independence in a time series of small counts within an Integer Autoregressive (INAR) model, taking a semiparametric approach that avoids any distributional assumption on the arrivals process of the model. The natur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d9b4475368ff73d808c2d88252fb646
https://doi.org/10.1017/s0266466618000403
https://doi.org/10.1017/s0266466618000403
Autor:
Brendan McCabe, Yao Rao
Publikováno v:
Economics Letters
In this paper, we examine the impact of increasing the size of a data set in detecting structural breaks. Based on an empirical application, supported by theoretical justification and a simulation experiment, we find that larger sample sizes may make
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8b11585765b833334639174817b1b50
https://doi.org/10.1016/j.econlet.2017.03.033
https://doi.org/10.1016/j.econlet.2017.03.033