Home > Research > Publications & Outputs > Predicting precipitation level

Electronic data

  • Fokianos_et_al-1996-Journal_of_Geophysical_Research%3A_Atmospheres

    Rights statement: An edited version of this paper was published by AGU. Copyright 1996 American Geophysical Union.

    Final published version, 382 KB, PDF document

Links

Text available via DOI:

View graph of relations

Predicting precipitation level

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

Standard

Predicting precipitation level. / Fokianos, K.; Kedem, B.; Short, D.A.
In: Journal of Geophysical Research: Atmospheres, Vol. 101, No. D21, 27.11.1996, p. 26473-26477.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Fokianos, K, Kedem, B & Short, DA 1996, 'Predicting precipitation level', Journal of Geophysical Research: Atmospheres, vol. 101, no. D21, pp. 26473-26477. https://doi.org/10.1029/96JD01386

APA

Fokianos, K., Kedem, B., & Short, D. A. (1996). Predicting precipitation level. Journal of Geophysical Research: Atmospheres, 101(D21), 26473-26477. https://doi.org/10.1029/96JD01386

Vancouver

Fokianos K, Kedem B, Short DA. Predicting precipitation level. Journal of Geophysical Research: Atmospheres. 1996 Nov 27;101(D21):26473-26477. doi: 10.1029/96JD01386

Author

Fokianos, K. ; Kedem, B. ; Short, D.A. / Predicting precipitation level. In: Journal of Geophysical Research: Atmospheres. 1996 ; Vol. 101, No. D21. pp. 26473-26477.

Bibtex

@article{ebf4a274a24448c2a6fcb945dd7416b4,
title = "Predicting precipitation level",
abstract = "We present a generalized logistic regression model for the statistical analysis of multicategorical time series. The model is suitably parameterized and partial likelihood inference is proposed for estimation of the unknown parameters. A goodness of fit statistic is derived to judge the quality of fit. The analysis is applied to data from the Tropical Ocean and Global Atmosphere/Coupled Ocean‐Atmosphere Response Experiment.",
author = "K. Fokianos and B. Kedem and D.A. Short",
year = "1996",
month = nov,
day = "27",
doi = "10.1029/96JD01386",
language = "English",
volume = "101",
pages = "26473--26477",
journal = "Journal of Geophysical Research: Atmospheres",
issn = "0747-7309",
publisher = "Wiley-Blackwell Publishing Ltd",
number = "D21",

}

RIS

TY - JOUR

T1 - Predicting precipitation level

AU - Fokianos, K.

AU - Kedem, B.

AU - Short, D.A.

PY - 1996/11/27

Y1 - 1996/11/27

N2 - We present a generalized logistic regression model for the statistical analysis of multicategorical time series. The model is suitably parameterized and partial likelihood inference is proposed for estimation of the unknown parameters. A goodness of fit statistic is derived to judge the quality of fit. The analysis is applied to data from the Tropical Ocean and Global Atmosphere/Coupled Ocean‐Atmosphere Response Experiment.

AB - We present a generalized logistic regression model for the statistical analysis of multicategorical time series. The model is suitably parameterized and partial likelihood inference is proposed for estimation of the unknown parameters. A goodness of fit statistic is derived to judge the quality of fit. The analysis is applied to data from the Tropical Ocean and Global Atmosphere/Coupled Ocean‐Atmosphere Response Experiment.

U2 - 10.1029/96JD01386

DO - 10.1029/96JD01386

M3 - Journal article

VL - 101

SP - 26473

EP - 26477

JO - Journal of Geophysical Research: Atmospheres

JF - Journal of Geophysical Research: Atmospheres

SN - 0747-7309

IS - D21

ER -