The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Renata Del Giudice Rodriguez - One of the best experts on this subject based on the ideXlab platform.
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Improved regionalization of streamflow by use of the streamflow equivalent of precipitation as an Explanatory Variable
Journal of Hydrology, 2013Co-Authors: Fernando Falco Pruski, Aline De Araújo Nunes, Pedro Lopes Pruski, Renata Del Giudice RodriguezAbstract:Summary Regionalization procedures are an important tool for estimating streamflow hydrography; however, there are difficulties associated with properly evaluating hydrological processes. This study aimed to propose a new Explanatory Variable for regionalization of the long-term average streamflow ( Q lt ) and permanent streamflow (present 95% of the time; Q 95 ). The physical characteristic used was the drainage area ( A ), and the climatic Variable considered was the annual rainfall, which was converted into the equivalent streamflow ( P eq ). Another Explanatory Variable was rainfall minus an abstraction value. This Variable ( P eq750 ) was also converted to streamflow. Use of P eq to replace A resulted in significant improvements in the statistical adjustment, particularly in the behavior of Q lt and Q 95 . The improvements were even more pronounced when using P eq750 , which caused the distribution of specific streamflows to behave more consistently.
Demetris Koutsoyiannis - One of the best experts on this subject based on the ideXlab platform.
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Bilinear surface smoothing for spatial interpolation with optional incorporation of an Explanatory Variable. Part 1: Theory
Hydrological Sciences Journal-journal Des Sciences Hydrologiques, 2016Co-Authors: Nikolaos Malamos, Demetris KoutsoyiannisAbstract:ABSTRACTBilinear surface smoothing is an alternative concept that provides flexible means for spatial interpolation. Interpolation is accomplished by means of fitting a bilinear surface into a regression model with known break points and adjustable smoothing terms. Additionally, as an option, the incorporation, in an objective manner, of the influence of an Explanatory Variable available at a considerable denser dataset is possible. The parameters involved in each case (with or without an Explanatory Variable) are determined by a nonparametric approach based on the generalized cross-validation (GCV) methodology. A convenient search technique for the smoothing parameters was achieved by transforming them in terms of tension parameters, with values restricted in the interval [0, 1). The mathematical framework, the computational implementation and details concerning both versions of the methodology, as well as practical aspects of their application are presented and discussed. In a companion paper, examples ...
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bilinear surface smoothing for spatial interpolation with optional incorporation of an Explanatory Variable part 2 application to synthesized and rainfall data
Hydrological Sciences Journal-journal Des Sciences Hydrologiques, 2016Co-Authors: Nikolaos Malamos, Demetris KoutsoyiannisAbstract:ABSTRACTThe non-parametric mathematical framework of bilinear surface smoothing (BSS) methodology provides flexible means for spatial (two dimensional) interpolation of Variables. As presented in a companion paper, interpolation is accomplished by means of fitting consecutive bilinear surface into a regression model with known break points and adjustable smoothing terms defined by means of angles formed by those bilinear surface. Additionally, the second version of the methodology (BSSE) incorporates, in an objective manner, the influence of an Explanatory Variable available at a considerably denser dataset. In the present study, both versions are explored and illustrated using both synthesized and real world (hydrological) data, and practical aspects of their application are discussed. Also, comparison and validation against the results of commonly used spatial interpolation methods (inverse distance weighted, spline, ordinary kriging and ordinary cokriging) are performed in the context of the real world...
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broken line smoothing for data series interpolation by incorporating an Explanatory Variable with denser observations application to soil water and rainfall data
Hydrological Sciences Journal-journal Des Sciences Hydrologiques, 2015Co-Authors: Nikolaos Malamos, Demetris KoutsoyiannisAbstract:AbstractBroken line smoothing is a simple technique for smoothing a broken line fit to observational data and provides a flexible means of interpolation. Here an extension of this technique is proposed, which can be utilized to perform various interpolation tasks, by incorporating, in an objective manner, an Explanatory Variable available at a considerably denser dataset than the initial main Variable. The technique incorporates smoothing terms with adjustable weights, defined by means of the angles formed by the consecutive segments of two broken lines. The mathematical framework and details of the method as well as practical aspects of its application are presented and discussed. Also, examples using both synthesized and real-world (soil water dynamics and hydrological) data are presented to explore and illustrate the methodology. Editor Z.W. Kundzewicz; Associate editor A. Carsteanu
Fernando Falco Pruski - One of the best experts on this subject based on the ideXlab platform.
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Improved regionalization of streamflow by use of the streamflow equivalent of precipitation as an Explanatory Variable
Journal of Hydrology, 2013Co-Authors: Fernando Falco Pruski, Aline De Araújo Nunes, Pedro Lopes Pruski, Renata Del Giudice RodriguezAbstract:Summary Regionalization procedures are an important tool for estimating streamflow hydrography; however, there are difficulties associated with properly evaluating hydrological processes. This study aimed to propose a new Explanatory Variable for regionalization of the long-term average streamflow ( Q lt ) and permanent streamflow (present 95% of the time; Q 95 ). The physical characteristic used was the drainage area ( A ), and the climatic Variable considered was the annual rainfall, which was converted into the equivalent streamflow ( P eq ). Another Explanatory Variable was rainfall minus an abstraction value. This Variable ( P eq750 ) was also converted to streamflow. Use of P eq to replace A resulted in significant improvements in the statistical adjustment, particularly in the behavior of Q lt and Q 95 . The improvements were even more pronounced when using P eq750 , which caused the distribution of specific streamflows to behave more consistently.
Babak Abbasi - One of the best experts on this subject based on the ideXlab platform.
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evaluation of process capability indices of linear profiles
International Journal of Quality & Reliability Management, 2012Co-Authors: Seyedeh Zahra Hosseinifard, Babak AbbasiAbstract:Purpose – In profile monitoring, which is a growing research area in the field of statistical process control, the relationship between response and Explanatory Variables is monitored over time. The purpose of this paper is to focus on the process capability analysis of linear profiles. Process capability indices give a quick indication of the capability of a manufacturing process.Design/methodology/approach – In this paper, the proportion of the non‐conformance criteria is employed to estimate process capability index. The paper has considered the cases where specification limits is constant or is a function of Explanatory Variable X. Moreover, cases where both equal and random design schemes in profile data acquisition is required (as the Explanatory Variable) is considered. Profiles with the assumption of deterministic design points are usually used in the calibration applications. However, there are other applications where design points within a profile would be i.i.d. random Variables from a given d...
Trevor S Harris - One of the best experts on this subject based on the ideXlab platform.
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earnings as an Explanatory Variable for returns
Journal of Accounting Research, 1991Co-Authors: Peter D Easton, Trevor S HarrisAbstract:In this paper we investigate whether the level of earnings divided by price at the beginning of the stock return period is relevant for evaluating earnings/returns associations.' The primary model motivating this research relies on the idea that book value (owners' equity) and market value are both "stock" Variables indicating the wealth of the firm's equity holders. The related "flow" Variables (after adjusting for dividends) are, respectively, earnings divided by price at the beginning of the return period (A/P-1) and market returns. It then follows that earnings divided by beginning of period price should be associated with stock returns. Although models based on a relation between market value and book value are used occasionally in the accounting research literature (see, for example, Landsman [1986], Harris and Ohlson [1987], and Barth
