Pre-seasonal temperature trend break dominating the trend break in autumn grassland phenology in China

Autor: Ning Qi, Yanzheng Yang, Guijun Yang, Weizhong Li, Chunjiang Zhao, Jun Zhao, Boheng Wang, Shaofeng Su, Pengxiang Zhao

Publikováno v: International Journal of Applied Earth Observations and Geoinformation, Vol 125, Iss , Pp 103590- (2023)

Interannual variations in the end of the growing season (EOS) play a crucial role in assessing carbon and energy cycling within grassland ecosystems. Previous studies have often fixed the trend breakpoint in autumn phenology around the year 2000 to e

Externí odkaz: https://doaj.org/article/50eb54a952f3444eb4f48d7655760c52

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GLS estimation and confidence sets for the date of a single break in models with trends

Autor: Eric Beutner, Yicong Lin, Stephan Smeekes

Publikováno v: Econometric Reviews, 42(2), 195-219. Taylor and Francis Ltd.
Beutner, E, Lin, Y & Smeekes, S 2023, ' GLS estimation and confidence sets for the date of a single break in models with trends ', Econometric Reviews, vol. 42, no. 2, pp. 195-219 . https://doi.org/10.1080/07474938.2023.2178088
Vrije Universiteit Amsterdam
Econometric Reviews, 42(2), 195-219. Routledge/Taylor & Francis Group

We develop a Feasible Generalized Least Squares estimator of the date of a structural break in level and/or trend. The estimator is based on a consistent estimate of a T-dimensional inverse autocovariance matrix. A cubic polynomial transformation of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3051fd4840bc070d1c566396908e7821
https://research.vu.nl/en/publications/7923ad8c-7074-4390-bfd2-af6fe1c819df

Unit roots and trend breaks in the Greek labor market

Autor: Ioannis A Venetis, Paraskevi K Salamaliki

Publikováno v: Journal of Economic Studies, 2015, Vol. 42, Issue 4, pp. 641-658.

Externí odkaz: http://www.emeraldinsight.com/doi/10.1108/JES-12-2013-0194

FPGA-embedded Linearized Bregman Iteration algorithm for trend break detection

Autor: Michael Lunglmayr, Felipe Calliari, Gustavo Castro do Amaral

Publikováno v: EURASIP Journal on Wireless Communications and Networking, Vol 2020, Iss 1, Pp 1-26 (2020)
Eurasip journal on wireless communications and networking, 2020(1)

Detection of level shifts in a noisy signal, or trend break detection, is a problem that appears in several research fields, from biophysics to optics and economics. Although many algorithms have been developed to deal with such a problem, accurate a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb12689a8eee1dee40e9307b5c5a2ca2
http://link.springer.com/article/10.1186/s13638-020-01796-0