scholarly journals The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 785 ◽  
Author(s):  
Fabio Caraffini ◽  
Giovanni Iacca
Keyword(s):  
Statistical Tests ◽  
Parameter Tuning ◽  
Stochastic Optimisation ◽  
Bonferroni Procedure ◽  
Current State ◽  
Processing Data ◽  
Wilcoxon Rank Sum Test ◽  
Algorithmic Design ◽  
Comparison Algorithms ◽  
Optimisation Algorithms

We present Stochastic Optimisation Software (SOS), a Java platform facilitating the algorithmic design process and the evaluation of metaheuristic optimisation algorithms. SOS reduces the burden of coding miscellaneous methods for dealing with several bothersome and time-demanding tasks such as parameter tuning, implementation of comparison algorithms and testbed problems, collecting and processing data to display results, measuring algorithmic overhead, etc. SOS provides numerous off-the-shelf methods including: (1) customised implementations of statistical tests, such as the Wilcoxon rank-sum test and the Holm–Bonferroni procedure, for comparing the performances of optimisation algorithms and automatically generating result tables in PDF and LATEX formats; (2) the implementation of an original advanced statistical routine for accurately comparing couples of stochastic optimisation algorithms; (3) the implementation of a novel testbed suite for continuous optimisation, derived from the IEEE CEC 2014 benchmark, allowing for controlled activation of the rotation on each testbed function. Moreover, we briefly comment on the current state of the literature in stochastic optimisation and highlight similarities shared by modern metaheuristics inspired by nature. We argue that the vast majority of these algorithms are simply a reformulation of the same methods and that metaheuristics for optimisation should be simply treated as stochastic processes with less emphasis on the inspiring metaphor behind them.

scholarly journals The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms

2020 ◽  
Author(s):  
Fabio Caraffini
Keyword(s):  
Statistical Tests ◽  
Parameter Tuning ◽  
Stochastic Optimisation ◽  
Bonferroni Procedure ◽  
Current State ◽  
Processing Data ◽  
Wilcoxon Rank Sum Test ◽  
Algorithmic Design ◽  
Comparison Algorithms ◽  
Optimisation Algorithms

The Stochastic Optimisation Software (SOS) is a Java platform facilitating the algorithmic design process and the evaluation of metaheuristic optimisation algorithms. It reduces the burden of coding miscellaneous methods for dealing with several bothersome and time-demanding tasks such as parameter tuning, implementation of comparison algorithms and testbed problems, collecting and processing data to display results, measuring algorithmic overhead, etc. SOS provides numerous off-the-shelf methods including 1) customised implementations of statistical tests, such as the Wilcoxon Rank-Sum test and the Holm-Bonferroni procedure, for comparing performances of optimisation algorithms and automatically generate result tables in PDF and LaTeX formats; 2) the implementation of an original advanced statistical routine for accurately comparing couples of stochastic optimisation algorithms; 3) the implementation of a novel testbed suite for continuous optimisation, derived from the IEEE CEC 2014 benchmark, allowing for controlled activation of the rotation operator. each testbed function. Moreover, this article comments on the current state of the literature in stochastic optimisation and highlights similarities shared by modern metaheuristics inspired by nature. It is argued that the vast majority of these algorithms are simply a reformulation of the same methods and that metaheuristics for optimisation should be simply treated as stochastic processes with less emphasis on the inspiring metaphor behind them.

scholarly journals Financial literacy of university students – the Czech and Slovak experience

2017 ◽  
Vol 4 (7) ◽  
pp. 41-51
Author(s):  
Ales Kozubik ◽  
Zuzana Kozubikova ◽  
Jiri Rybicka
Keyword(s):  
Statistical Analysis ◽  
University Students ◽  
Financial Literacy ◽  
Questionnaire Survey ◽  
Statistical Tests ◽  
Personal Characteristics ◽  
Modern Society ◽  
The Self ◽  
European Countries ◽  
Current State

Financial literacy is one of the key components of education for living in a modern society. In this article, we present the results of our research into the current state of financial literacy among university students from two European countries. Our research was conducted in the form of a questionnaire survey. In the first part of the questionnaire we investigated selected personal characteristics of respondents and the second part was devoted to knowledge in different areas of financial literacy. The knowledge questions were focused mainly on respondents’ competence in specific practical situations. The obtained data were processed by statistical analysis, including the dependencies between the results of the knowledge part and the self-reflexive assessment in the first part of the questionnaire. This analysis revealed several noteworthy findings. Keywords: Financial literacy; questionnaire survey; statistical tests;

Genetic structure and variability in Pinusstrobus in Quebec

1994 ◽  
Vol 24 (8) ◽  
pp. 1726-1733 ◽  
Author(s):  
J. Beaulieu ◽  
J.-P. Simon
Keyword(s):  
Genetic Diversity ◽  
Statistical Tests ◽  
Natural Populations ◽  
Genetic Distances ◽  
White Pine ◽  
Eastern White Pine ◽  
Improvement Program ◽  
Bonferroni Procedure ◽  
Natural Range ◽  
Very High

The level of genetic diversity of natural populations of eastern white pine (Pinusstrobus L.) from Quebec was estimated from allozyme variants of 18 loci coding 12 enzyme systems. On average, a white pine population was polymorphic at 50.6% of loci, had 1.96 alleles and 1.22 effective alleles per locus, and observed and expected heterozygosities of 0.176 and 0.180, respectively. The level of genetic diversity was lower in the populations of the St. Lawrence lowlands than in those of western Quebec. This observation will help in guiding the selection program of the eastern white pine improvement program under way in Quebec. Genetic differentiation among sampled populations was weak and accounted for only 2% of the total diversity. The estimate of gene flow was very high, resulting in low values for genetic distances among populations. Only one locus showed a heterogeneity of allelic frequencies among populations after the Bonferroni procedure was applied for simultaneous statistical tests. A cluster analysis based on genetic distances among populations revealed that the Anticosti and Abitibi populations, located at the limit of the natural range of white pine, were similar to populations from regions that were geographically the most distant.

The Long Way From α-Error Control to Validity Proper

2012 ◽  
Vol 7 (6) ◽  
pp. 661-669 ◽  
Author(s):  
Klaus Fiedler ◽  
Florian Kutzner ◽  
Joachim I. Krueger
Keyword(s):  
Error Control ◽  
Behavioral Science ◽  
Statistical Tests ◽  
Inductive Reasoning ◽  
Empirical Science ◽  
Scientific Culture ◽  
Current State ◽  
Alternative Hypotheses ◽  
Survey Results ◽  
State Of Affairs

Several influential publications have sensitized the community of behavioral scientists to the dangers of inflated effects and false-positive errors leading to the unwarranted publication of nonreplicable findings. This issue has been related to prominent cases of data fabrication and survey results pointing to bad practices in empirical science. Although we concur with the motives behind these critical arguments, we note that an isolated debate of false positives may itself be misleading and counter-productive. Instead, we argue that, given the current state of affairs in behavioral science, false negatives often constitute a more serious problem. Referring to Wason’s (1960) seminal work on inductive reasoning, we show that the failure to assertively generate and test alternative hypotheses can lead to dramatic theoretical mistakes, which cannot be corrected by any kind of rigor applied to statistical tests of the focal hypotheses. We conclude that a scientific culture rewarding strong inference (Platt, 1964) is more likely to see progress than a culture preoccupied with tightening its standards for the mere publication of original findings.

scholarly journals Can Compact Optimisation Algorithms Be Structurally Biased?

2020 ◽  
Author(s):  
Anna V. Kononova ◽  
Fabio Caraffini ◽  
Hao Wang ◽  
Thomas Bäck
Keyword(s):  
Search Space ◽  
Test Cases ◽  
Estimation Of Distribution Algorithms ◽  
Test Function ◽  
Stochastic Optimisation ◽  
Estimation Of Distribution ◽  
Distribution Algorithms ◽  
Anderson Darling ◽  
Optimisation Algorithms

In the field of stochastic optimisation, the so-called structural bias constitutes an undesired behaviour of an algorithm that is unable to explore the search space to a uniform extent. In this paper, we investigate whether algorithms from a subclass of estimation of distribution algorithms, the compact algorithms, exhibit structural bias. Our approach, justified in our earlier publications, is based on conducting experiments on a test function whose values are uniformly distributed in its domain. For the experiment, 81 combinations of compact algorithms and strategies of dealing with infeasible solutions have been selected as test cases. We have applied two approaches for determining the presence and severity of structural bias, namely a visual and a statistical (Anderson-Darling) tests. Our results suggest that compact algorithms are more immune to structural bias than their counterparts maintaining explicit populations. Both tests indicate that strong structural bias is found only in one of the algorithms (cBFO) regardless of the choice of strategy of dealing with infeasible solutions and cPSO mirror. For other test cases, statistical and visual tests disagree on some cases classified as having mild or strong structural bias: the former one tends to make harsher decisions, thus needing further investigation.

The Application of the Time Series Theory to Processing Data From the SBAS Receiver in Safety Mode

2012 ◽  
Author(s):  
M. Jonas
Keyword(s):  
Time Series ◽  
Statistical Tests ◽  
Point Of View ◽  
Garch Models ◽  
Autocorrelation Functions ◽  
Conditional Heteroscedasticity ◽  
New Methods ◽  
Processing Data ◽  
Wide Area Augmentation System ◽  
The Usa

Before satellite-based augmentation systems (SBAS) such as the Wide Area Augmentation System (WAAS) in the USA, and the European Geostationary Navigation Overlay Service (EGNOS), will be used in railway safety-related applications, it is necessary to determine reliability attributes of these systems as quality measures from the user’s point of view. It is necessary to find new methods of processing data from the SBAS system in accordance with strict railway standards. For this purposes data from the SBAS receiver with the Safety of Life Service was processed by means of the time series theory. At first, a basic statistic exploration analysis by means of histograms and boxplot graphs was done. Then correlation analysis by autocorrelation (ACF), and partial autocorrelation functions (PACF), was done. Statistical tests for the confirmation of non-stationarity, and conditional heteroscedasticity of time series were done. Engle’s ARCH test confirmed that conditional heteroscedasticity is contained. ARMA/GARCH models were constructed, and their residuals were analyzed. Autocorrelation functions and statistical tests of models residuals were done. The analysis implies that the models well cover the variance volatility of investigated time series and so it is possible to use the ARMA/GARCH models for the modeling of SBAS receiver outputs.

Is There Significance beyond the T-Test?

1988 ◽  
Vol 22 (4) ◽  
pp. 334-335 ◽  
Author(s):  
Eric G. Boyce ◽  
Jean M. Nappi
Keyword(s):  
Training Programs ◽  
Statistical Tests ◽  
Nonparametric Tests ◽  
Statistical Test ◽  
T Test ◽  
Wilcoxon Rank Sum Test ◽  
Continuous Scale ◽  
Parametric Statistical Test ◽  
And Training ◽  
Normally Distributed

Choosing the most appropriate statistical test may be routine for statisticians, but not for clinicians. The t-test, a parametric statistical test, may be used inappropriately. This commentary describes the assumptions of and alternatives to the t-test. T-tests are used to compare two groups of data that are from a continuous scale and normally distributed. Determining if data are normally distributed can be difficult but selected methods can be useful. Two nonparametric tests, the Mann-Whitney U test and the Wilcoxon rank sum test, may be more appropriate in analyzing data that are neither continuous nor normally distributed. Statistical results may vary with the test chosen. Investigators are responsible for using the appropriate statistical tests. Statisticians and texts can be consulted. Pharmacy educational and training programs may need further emphasis in the area of statistics.

scholarly journals Validity and Reliability of Physiological Data in Applied Settings Measured by Wearable Technology: A Rapid Systematic Review

Technologies ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 70
Author(s):  
Bryson Carrier ◽  
Brenna Barrios ◽  
Brayden D. Jolley ◽  
James W. Navalta
Keyword(s):  
Statistical Tests ◽  
Meta Analysis ◽  
Analytical Techniques ◽  
Physiological Data ◽  
Percentage Error ◽  
Validity And Reliability ◽  
Intra Class Correlation ◽  
Current State ◽  
Outdoor Environments ◽  
Study Designs

The purpose of this review was to evaluate the current state of the literature and to identify the types of study designs, wearable devices, statistical tests, and exercise modes used in validation and reliability studies conducted in applied settings/outdoor environments. This was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We identified nine articles that fit our inclusion criteria, eight of which tested for validity and one tested for reliability. The studies tested 28 different devices with exercise modalities of running, walking, cycling, and hiking. While there were no universally common analytical techniques used to measure accuracy or validity, correlative measures were used in 88% of studies, mean absolute percentage error (MAPE) in 75%, and Bland–Altman plots in 63%. Intra-class correlation was used to determine reliability. There were not any universally common thresholds to determine validity, however, of the studies that used MAPE and correlation, there were only five devices that had a MAPE of < 10% and a correlation value of > 0.7. Overall, the current review establishes the need for greater testing in applied settings when validating wearables. Researchers should seek to incorporate multiple intensities, populations, and modalities into their study designs while utilizing appropriate analytical techniques to measure and determine validity and reliability.

Pseudo-precision in Gene Expression Values Can Reduce Efficiency

2007 ◽  
Vol 46 (05) ◽  
pp. 538-541 ◽  
Author(s):  
T. Boes ◽  
K.-H. Jöckel ◽  
M. Neuhäuser
Keyword(s):  
Statistical Tests ◽  
Random Noise ◽  
Nonparametric Tests ◽  
P Value ◽  
Data Sets ◽  
Expression Of Genes ◽  
Efficient Test ◽  
Wilcoxon Rank Sum Test ◽  
Scanned Images ◽  
Level Analysis

Summary Objectives: When estimating the expression of genes based on the scanned images from microarrays various algorithms are applied in a so-called low-level analysis which can calculate expression values with an arbitrary number of digits beyond the decimal point. However, too many digits (decimal places) are usually not justified because they do not represent the precision of the measured expression. Thus, there is pseudo-precision and, as a result, there are no tied values. Methods: We suggest avoiding, or omitting, the pseudo-precision: ties can remain, or be created by rounding the computed expression values. Then, average ranks can be used in order to apply nonparametric tests when ties occur. We use two actual data sets and the Wilcoxon rank sum test. Results: We demonstrate that rounding gives a more efficient test, i.e. the average p-value is decreased and the number of p-values smaller than 0.05 is increased. Conclusions: The random noise of pseudo-precision can reduce the efficiency of statistical tests applied to detect differentially expressed genes. This result is, obviously, relevant in many other areas of our digitalized world.

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