scholarly journals Monte Carlo Statistical Tests for Identity of Theoretical and Empirical Distributions of Experimental Data

10.5772/53049 ◽  
2013 ◽  
Author(s):  
Natalia D. ◽  
Daniela Toneva-Zheynova ◽  
Krasimir Kolev ◽  
Kiril Tenekedjiev
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Statistical Tests ◽  
Empirical Distributions

scholarly journals A Simulation of the Effects of Badminton Serve Release Height

2021 ◽  
Vol 11 (7) ◽  
pp. 2903
Author(s):  
John Rasmussen ◽  
Mark de Zee
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
World Federation ◽  
Forward Dynamics ◽  
Dynamics Model ◽  
Rib Cage ◽  
Female Player ◽  
Ballistic Trajectory ◽  
Release Height

In this work, we develop and calibrate a model to represent the trajectory of a badminton shuttlecock and use it to investigate the influence of serve height in view of a new serve rule instated by the Badminton World Federation. The new rule means that all players must launch the shuttlecock below a height of 1.15 m, as opposed to the old rule whereby the required launch height was under the rib cage of the server. The model is based on a forward dynamics model of ballistic trajectory with drag, and it is calibrated with experimental data. The experiments also served to determine the actual influence of the new rule on the shuttlecock launch position. The model is used in a Monte Carlo simulation to determine the statistical influence of the new serve rules on the player’s ability to perform good serves; i.e., serves with little opportunity for the receiver to attack. We conclude that, for the female player in question, serving below a height of 1.15 m makes it marginally more difficult to perform excellent serves. We also conclude that there might be alternative launch positions that would be less likely to produce the best serves but could be exploited as a tactical option.

scholarly journals Statistical Tests of Symbolic Dynamics

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 817
Author(s):  
Fernando López ◽  
Mariano Matilla-García ◽  
Jesús Mur ◽  
Manuel Ruiz Marín
Keyword(s):  
Monte Carlo ◽  
Symbolic Dynamics ◽  
Null Hypothesis ◽  
Statistical Tests ◽  
General Applicability ◽  
Monte Carlo Experiments ◽  
The Mean ◽  
Theoretical Application ◽  
New Statistics ◽  
General Method

A novel general method for constructing nonparametric hypotheses tests based on the field of symbolic analysis is introduced in this paper. Several existing tests based on symbolic entropy that have been used for testing central hypotheses in several branches of science (particularly in economics and statistics) are particular cases of this general approach. This family of symbolic tests uses few assumptions, which increases the general applicability of any symbolic-based test. Additionally, as a theoretical application of this method, we construct and put forward four new statistics to test for the null hypothesis of spatiotemporal independence. There are very few tests in the specialized literature in this regard. The new tests were evaluated with the mean of several Monte Carlo experiments. The results highlight the outstanding performance of the proposed test.

scholarly journals High energy cosmic ray interactions and UHECR composition problem

2019 ◽  
Vol 210 ◽  
pp. 02001
Author(s):  
Sergey Ostapchenko
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Cosmic Rays ◽  
Cosmic Ray ◽  
High Energy ◽  
Ultra High Energy ◽  
Hadronic Interactions ◽  
High Energy Cosmic Rays ◽  
Cosmic Ray Interactions ◽  
Composition Problem

The differences between contemporary Monte Carlo generators of high energy hadronic interactions are discussed and their impact on the interpretation of experimental data on ultra-high energy cosmic rays (UHECRs) is studied. Key directions for further model improvements are outlined. The prospect for a coherent interpretation of the data in terms of the UHECR composition is investigated.

Monte Carlo backscattering yield (BY) calculations applying continuous slowing down approximation (CSDA) and experimental data

Vacuum ◽  
2007 ◽  
Vol 82 (2) ◽  
pp. 201-204 ◽  
Author(s):  
L. Zommer ◽  
A. Jablonski ◽  
G. Gergely ◽  
S. Gurban
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Slowing Down

Analyzing Herbicide Interactions: A Statistical Treatment of Colby's Method

1988 ◽  
Vol 2 (3) ◽  
pp. 304-309 ◽  
Author(s):  
Jerry L. Flint ◽  
Paul L. Cornelius ◽  
Michael Barrett
Keyword(s):  
Experimental Data ◽  
Statistical Tests ◽  
Statistical Treatment ◽  
Measurement Scale ◽  
Growth Data ◽  
Significance Tests ◽  
Anova Model ◽  
Heterogeneity Of Variance ◽  
Original Measurement ◽  
Data Heterogeneity

A model and a proposed method for testing herbicide interactions were modified from an analysis of variance (ANOVA) model for a 2 by 2 factorial experiment. Statistical tests for either synergism, antagonism, or additivity of herbicide combinations were developed through transforming growth data to logarithms followed by significance tests of 2 by 2 contrasts of the form μii- μi0- μ0i+ μ00with respect to the log-transformed data. Using actual experimental data, heterogeneity of variance was less severe on the log scale compared to the original measurement scale. An expedient SAS(R)program for obtaining the desired significance tests was developed.

MODELLING OF 226Ra ACTIVITY CONCENTRATIONS ALONG OGUN RIVER, SOUTH WESTERN NIGERIA

2018 ◽  
Vol 14 (2) ◽  
pp. 1-14
Author(s):  
I C OKEYODE ◽  
N N JIBIRI ◽  
R BELLO
Keyword(s):  
Experimental Data ◽  
Gamma Ray ◽  
Statistical Tests ◽  
Least Square ◽  
Approximation Technique ◽  
Sediment Samples ◽  
Gamma Ray Spectrometer ◽  
Activity Concentrations ◽  
226Ra Activity ◽  
Ogun River

This work was aimed at generating a model using least square approximation technique to predict values of activity concentrations of 226Ra in any location along Ogun river in Nigeria using experimental data. Sediment samples were collected in thirty two locations along the river of about 400 km in length. NaI(Tl) gamma-ray spectrometer system was used to obtain activity concentrations of 226Ra.The aver-age value of activity concentration of 226Ra in the sediment samples from the upper region through the middle to the lower region of the river was found to be 12.65 ± 3.48 Bq/kg, having values ranging from 5.57 ± 2.36 Bq/kg (at Ekerin) to 20.40 ± 4.52 Bq/kg (at Sokori). From this work, it was observed that the generated model and experimental data could be used to predict values of activity concentrations of 226Ra in any location along the river once the latitude and longitude (position) are known. Statistical tests on the model also showed that there were no significant differences between the experimental and predicted data of 226Ra and that 98.70% of the experimental data were predicted by the model.

Statistical tests of differential susceptibility: Performance, limitations, and improvements

2017 ◽  
Vol 29 (4) ◽  
pp. 1267-1278 ◽  
Author(s):  
Marco Del Giudice
Keyword(s):  
Monte Carlo ◽  
Statistical Approach ◽  
Statistical Tests ◽  
Differential Susceptibility ◽  
Initial Response ◽  
Empirical Literature ◽  
False Negatives ◽  
Interaction Index ◽  
Future Studies ◽  
Highly Sensitive

AbstractStatistical tests of differential susceptibility have become standard in the empirical literature, and are routinely used to adjudicate between alternative developmental hypotheses. However, their performance and limitations have never been systematically investigated. In this paper I employ Monte Carlo simulations to explore the functioning of three commonly used tests proposed by Roisman et al. (2012). Simulations showed that critical tests of differential susceptibility require considerably larger samples than standard power calculations would suggest. The results also showed that existing criteria for differential susceptibility based on the proportion of interaction index (i.e., values between .40 and .60) are especially likely to produce false negatives and highly sensitive to assumptions about interaction symmetry. As an initial response to these problems, I propose a revised test based on a broader window of proportion of interaction index values (between .20 and .80). Additional simulations showed that the revised test outperforms existing tests of differential susceptibility, considerably improving detection with little effect on the rate of false positives. I conclude by noting the limitations of a purely statistical approach to differential susceptibility, and discussing the implications of the present results for the interpretation of published findings and the design of future studies in this area.

scholarly journals A Monte Carlo approach for determining cluster evaporation rates from concentration measurements

2016 ◽  
Author(s):  
Oona Kupiainen-Määttä
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Markov Chain ◽  
Sulfuric Acid ◽  
Markov Chain Monte Carlo ◽  
Mass Spectrometer ◽  
Large Fraction ◽  
Cluster Formation ◽  
Unknown Parameters ◽  
Ammonia Clusters

Abstract. Evaporation rates of small negatively charged sulfuric acid–ammonia clusters are determined by combining detailed cluster formation simulations with cluster distributions measured at CLOUD. The analysis is performed by varying the evaporation rates with Markov chain Monte Carlo (MCMC), running cluster formation simulations with each new set of evaporation rates and comparing the obtained cluster distributions to the measurements. In a second set of simulations, the fragmentation of clusters in the mass spectrometer due to energetic collisions is studied by treating also the fragmentation probabilities as unknown parameters and varying them with MCMC. This second set of simulations results in a better fit to the experimental data, suggesting that a large fraction of the observed HSO4− and HSO4− ⋅ H2SO4 signals may result from fragmentation of larger clusters, most importantly the HSO4− ⋅ (H2SO4)2 trimer.

scholarly journals A Monte-Carlo Simulation of the Behaviour of Electron Swarms in Hydrogen Using an Anisotropic Scattering Model

1978 ◽  
Vol 31 (4) ◽  
pp. 299 ◽  
Author(s):  
HA Blevin ◽  
J Fletcher ◽  
SR Hunter
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Electron Transport ◽  
Anisotropic Scattering ◽  
Isotropic Scattering ◽  
Transport Parameters ◽  
Simulation Code ◽  
Scattering Model ◽  
Good Agreement

Hunter (1977) found that a Monte-Carlo simulation of electron swarms in hydrogen, based on an isotropic scattering model, produced discrepancies between the predicted and measured electron transport parameters. The present paper shows that, with an anisotropic scattering model, good agreement is obtained between the predicted and experimental data. The simulation code is used here to calculate various parameters which are not directly measurable.

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