scholarly journals Dual-Polarized Planar Phased Array Analysis for Meteorological Applications

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Chen Pang ◽  
Peter Hoogeboom ◽  
François Le Chevalier ◽  
Herman W. J. Russchenberg ◽  
Jian Dong ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Measurement Error ◽  
Theoretical Analysis ◽  
Monte Carlo Simulations ◽  
Phased Array ◽  
Antenna Element ◽  
Array Analysis ◽  
Dual Polarized ◽  
Dual Polarized Antenna ◽  
Entire Array

This paper presents a theoretical analysis for the accuracy requirements of the planar polarimetric phased array radar (PPPAR) in meteorological applications. Among many factors that contribute to the polarimetric biases, four factors are considered and analyzed in this study, namely, the polarization distortion due to the intrinsic limitation of a dual-polarized antenna element, the antenna pattern measurement error, the entire array patterns, and the imperfect horizontal and vertical channels. Two operation modes, the alternately transmitting and simultaneously receiving (ATSR) mode and the simultaneously transmitting and simultaneously receiving (STSR) mode, are discussed. For each mode, the polarimetric biases are formulated. As the STSR mode with orthogonal waveforms is similar to the ATSR mode, the analysis is mainly focused on the ATSR mode and the impacts of the bias sources on the measurement of polarimetric variables are investigated through Monte Carlo simulations. Some insights of the accuracy requirements are obtained and summarized.

scholarly journals An Updated Guideline for Assessing Discriminant Validity

2020 ◽  
pp. 109442812096861
Author(s):  
Mikko Rönkkö ◽  
Eunseong Cho
Keyword(s):  
Monte Carlo ◽  
Measurement Error ◽  
Monte Carlo Simulations ◽  
Empirical Research ◽  
Discriminant Validity ◽  
Ad Hoc ◽  
Validity Assessment ◽  
Two Measures ◽  
Definition Of

Discriminant validity was originally presented as a set of empirical criteria that can be assessed from multitrait-multimethod (MTMM) matrices. Because datasets used by applied researchers rarely lend themselves to MTMM analysis, the need to assess discriminant validity in empirical research has led to the introduction of numerous techniques, some of which have been introduced in an ad hoc manner and without rigorous methodological support. We review various definitions of and techniques for assessing discriminant validity and provide a generalized definition of discriminant validity based on the correlation between two measures after measurement error has been considered. We then review techniques that have been proposed for discriminant validity assessment, demonstrating some problems and equivalencies of these techniques that have gone unnoticed by prior research. After conducting Monte Carlo simulations that compare the techniques, we present techniques called CICFA(sys) and [Formula: see text](sys) that applied researchers can use to assess discriminant validity.

scholarly journals Testing for the presence of measurement error in Stata

2020 ◽  
Vol 20 (2) ◽  
pp. 382-404
Author(s):  
Young Jun Lee ◽  
Daniel Wilhelm
Keyword(s):  
Monte Carlo ◽  
Measurement Error ◽  
Monte Carlo Simulations ◽  
Nonparametric Test ◽  
Parametric Models ◽  
Empirical Application ◽  
Explanatory Variables ◽  
Working Paper ◽  
Linear Regressions

In this article, we describe how to test for the presence of measurement error in explanatory variables. First, we discuss the test of such hypotheses in parametric models such as linear regressions and then introduce a new command, dgmtest, for a nonparametric test proposed in Wilhelm (2018, Working Paper CWP45/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies). To illustrate the new command, we provide Monte Carlo simulations and an empirical application to testing for measurement error in administrative earnings data.

KINETIC ROUGHENING AND INTERACTING REACTING SPECIES: NONLINEAR ASPECTS

Fractals ◽  
1993 ◽  
Vol 01 (03) ◽  
pp. 470-474 ◽  
Author(s):  
I.M. SOKOLOV ◽  
P. ARGYRAKIS ◽  
A. BLUMEN
Keyword(s):  
Monte Carlo ◽  
Theoretical Analysis ◽  
Diffusion Process ◽  
Monte Carlo Simulations ◽  
Short Range ◽  
Reaction Diffusion ◽  
Kinetic Roughening ◽  
Constant Rate ◽  
Good Agreement

We consider the A+B→0 reaction, in which particles interact through short-range forces. The analysis leads to expressions akin in form to those which describe kinetic roughening. In a situation in which particles are generated with a constant rate j0, their concentration n(t) grows as [Formula: see text] in d=1. Here the theoretical analysis predicts γ=1/5 and β=2/5, in very good agreement with direct Monte-Carlo simulations of the reaction-diffusion process.

scholarly journals Numerical preservation issues in stochastic dynamical systems by $ \vartheta $-methods

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Raffaele D'Ambrosio ◽  
Stefano Di Giovacchino
Keyword(s):  
Monte Carlo ◽  
Dynamical Systems ◽  
Theoretical Analysis ◽  
Monte Carlo Simulations ◽  
Duffing Oscillator ◽  
Stochastic Dynamical Systems ◽  
Numerical Evidence ◽  
Stochastic Oscillator ◽  
Expected Values

<p style='text-indent:20px;'>This paper analyzes conservation issues in the discretization of certain stochastic dynamical systems by means of stochastic <inline-formula><tex-math id="M2">\begin{document}$ \vartheta $\end{document}</tex-math></inline-formula>-mehods. The analysis also takes into account the effects of the estimation of the expected values by means of Monte Carlo simulations. The theoretical analysis is supported by a numerical evidence on a given stochastic oscillator, inspired by the Duffing oscillator.</p>

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