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Technical Note: a Significance Test for Data-sparse Zones in Scatter Plots : Volume 9, Issue 1 (26/01/2012)

By Vetrova, V. V.

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Book Id: WPLBN0004013175
Format Type: PDF Article :
File Size: Pages 9
Reproduction Date: 2015

Title: Technical Note: a Significance Test for Data-sparse Zones in Scatter Plots : Volume 9, Issue 1 (26/01/2012)  
Author: Vetrova, V. V.
Volume: Vol. 9, Issue 1
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2012
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Bardsley, W. E., & Vetrova, V. V. (2012). Technical Note: a Significance Test for Data-sparse Zones in Scatter Plots : Volume 9, Issue 1 (26/01/2012). Retrieved from http://worldebookfair.com/


Description
Description: Department of Earth & Ocean Sciences, University of Waikato, Hamilton, New Zealand. Data-sparse zones in scatter plots of hydrological variables can be of interest in various contexts. For example, a well-defined data-sparse zone may indicate inhibition of one variable by another. It is of interest therefore to determine whether data-sparse regions in scatter plots are of sufficient extent to be beyond random chance. We consider the specific situation of data-sparse regions defined by a linear internal boundary within a scatter plot defined over a rectangular region. An Excel VBA macro is provided for carrying out a randomisation-based significance test of the data-sparse region, taking into account both the within-region number of data points and the extent of the region. Example applications are given with respect to a rainfall time series from Israel and to validation scatter plots from a seasonal forecasting model for lake inflows in New Zealand.

Summary
Technical Note: A significance test for data-sparse zones in scatter plots

Excerpt
Kumbhakar, S. C., Byeong, U. P., Simar, L., and Efthymios, G. T.: Nonparametric stochastic frontiers: a local maximum likelihood approach, J. Econometr., 137, 1–27, 2007.; Bardsley, W. E. and Purdie, J.: An invalidation test for predictive models, J. Hydrol., 338, 57–62, 2007.; Bardsley, W. E., Jorgensen, M. A., Alpert, P., and Ben-Gai, T.: A significance test for empty corners in scatter diagrams, J. Hydrol., 219, 1–6, 1999.; Delaigle, A. and Gijbels, I.: Data-driven boundary estimation in deconvolution problems, Comput. Stat. Data Anal., 50, 1965–1994, 2006.; Florens, J.-P. and Simar, L.: Parametric approximations of nonparametric frontiers, J. Econometr., 124, 91–116, 2005.; Green, M. B. and Finlay, J. C.: Detecting characteristic hydrological and biogeochemical signals through nonparametric scatter plot analysis of normalized data, Water Resour. Res., 44, W08455, doi:10.1029/2007WR006509, 2008.; Hall, P. and Simar, L.: Estimating a changepoint, boundary, or frontier in the presence of observation error, J. Am. Stat. Assoc., 97, 523–534, 2002.

 

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