Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Jose M. Peña"'
Publikováno v:
Agricultural Water Management, Vol 286, Iss , Pp 108393- (2023)
Water is the main limiting factor for olive cultivation in rainfed conditions. In irrigated orchards, water availability is scarce mainly during drought periods. Thus, increasing irrigation efficiency is a key issue to improve water management, espec
Externí odkaz:
https://doaj.org/article/51c759b8e6cc40e5866e64d91a869263
Publikováno v:
Agronomy, Vol 12, Iss 4, p 756 (2022)
Water deficit, especially during summer, is currently one of the most important stress factors that influence olive oil production in olive orchards. A precision irrigation strategy, based on daily trunk growth, was assessed and compared with one con
Externí odkaz:
https://doaj.org/article/3b228a19347e40d898b5ca8699ca691a
Publikováno v:
Remote Sensing, Vol 13, Iss 11, p 2139 (2021)
This paper reviewed a set of twenty-one original and innovative papers included in a special issue on UAVs for vegetation monitoring, which proposed new methods and techniques applied to diverse agricultural and forestry scenarios. Three general cate
Externí odkaz:
https://doaj.org/article/9f33fcac686a4250aed637e878a59b39
Publikováno v:
Remote Sensing, Vol 12, Iss 20, p 3424 (2020)
Precision agriculture (PA) is a management strategy that analyzes the spatial and temporal variability of agricultural fields using information and communication technologies with the aim to optimize profitability, sustainability, and protection of a
Externí odkaz:
https://doaj.org/article/7ab7bde9104a455f8279442d1abfc2d1
Autor:
Ana I. de Castro, Jorge Torres-Sánchez, Jose M. Peña, Francisco M. Jiménez-Brenes, Ovidiu Csillik, Francisca López-Granados
Publikováno v:
Remote Sensing, Vol 10, Iss 2, p 285 (2018)
Accurate and timely detection of weeds between and within crop rows in the early growth stage is considered one of the main challenges in site-specific weed management (SSWM). In this context, a robust and innovative automatic object-based image anal
Externí odkaz:
https://doaj.org/article/615378195a53406ca068c665970ee35f
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:11810-11818
Structural Equation/Causal Models (SEMs/SCMs) are widely used in epidemiology and social sciences to identify and analyze the average causal effect (ACE) and conditional ACE (CACE). Traditional causal effect estimation methods such as Inverse Probabi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11339870bee52fc9e8a2ff34cf1c8cef
https://doi.org/10.1609/aaai.v36i11.21437
https://doi.org/10.1609/aaai.v36i11.21437
Autor:
Jose M. Peña
Publikováno v:
Journal of Causal Inference, Vol 8, Iss 1, Pp 150-163 (2020)
Suppose that we are interested in the average causal effect of a binary treatment on an outcome when this relationship is confounded by a binary confounder. Suppose that the confounder is unobserved but a nondifferential proxy of it is observed. We s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26825b7339605e43bc163c7a3593e553
https://doi.org/10.1515/jci-2020-0014
https://doi.org/10.1515/jci-2020-0014
Publikováno v:
Gabriel, E E, Peña, J M & Sjölander, A 2022, ' Bias attenuation results for dichotomization of a continuous confounder ', Journal of Causal Inference, vol. 10, no. 1, pp. 515-526 . https://doi.org/10.1515/jci-2022-0047
It is well-known that dichotomization can cause bias and loss of efficiency in estimation. One can easily construct examples where adjusting for a dichotomized confounder causes bias in causal estimation. There are additional examples in the literatu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7737fd8ddec2ae8cea64c97ac9259d16
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-192000
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-192000
Suppose we want to estimate the causal effect of an exposure on an outcome, while adjusting for a binary confounder. Suppose that the confounder is measured with error, but that the measurement error is nondifferential. We show that, under certain as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c22671881244cc379e48a463046786b
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-184988
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-184988
Publikováno v:
Journal of Causal Inference, Vol 9, Iss 1, Pp 229-249 (2021)
Biological and epidemiological phenomena are often measured with error or imperfectly captured in data. When the true state of this imperfect measure is a confounder of an outcome exposure relationship of interest, it was previously widely believed t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2314c7e6cb17960bab987cc076a9672
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-181213
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-181213