Variance Ratio Research Articles

Efficient estimation of the number of clusters for high-dimension data

The exponential growth of digital image data has given rise to the need of efficient content management and retrieval tools. Currently, there is a lack of tools for processing the collected unlabeled data in a schematic manner. K-means is one of the most widely used clustering methods and has been applied in a variety of fields, one of them being image sorting. Although a useful tool for image management, the K-means method is heavily influenced by initializations, the most important one being the need to know the number of clusters a priori. A number of different methods have been proposed for identifying the correct number of clusters for K-means, one of them being the variance ratio criterion (VRC). Despite its popularity, the VRC method comes with two very important shortcomings: it only yields good results when the data dimensionality is low and it does not scale well for a high number of clusters, making it very difficult to use in computer vision applications. We propose an extension to the VRC method that works for increased cluster number and high-dimensionality data sets and therefore is fit for image data sets.

The Dynamics of the Impact of the Covid-19 Pandemic on Pan-Asia’s Real Estate Investment Trusts

Abstract This study evaluated the dynamics of Real Estate Investment Trusts (REITs) in Pan-Asian countries impacted by COVID-19. The countries comprised Malaysia, Thailand, Indonesia, Singapore, Vietnam, South Korea, Japan, China, the Philippines, and Hong Kong. The study aimed to understand how the global crisis affected the real estate industry, specifically publicly traded companies. The COVID-19 pandemic significantly impacted many industries worldwide, including real estate. It caused changes in supply and demand dynamics, disrupted business operations and affected economic activity. The pandemic has also caused a general economic slowdown, with businesses struggling and unemployment rates increasing in some countries in Asia. This in turn has led to reduced consumer spending and lower demand for all types of properties, impacting the overall performance of the Asian REITs market. This study employed techniques such as Sharpe ratio, variance ratio, and Analysis of Variance (ANOVA) to highlight the dynamics of Asian REITs towards the impact of COVID-19. The findings revealed that all Asian countries were severely impacted by COVID-19, with Japan REITs experiencing the highest drop and Taiwan REITs experiencing the lowest decline.

Does Random Auction Ending Curb Stock Price Manipulation?

This paper examines the effect on stock market efficiency and potential market manipulation of introducing a random ending time for the call auctions that start and end continuous trading on three equity markets. We find that the probability of a price dislocation at the end of the auction declines, indicating a lower risk of market manipulation. In addition, the variance ratio and market-adjusted return volatility measures decrease, suggesting a more efficient and less volatile price discovery process. We confirm a behavioral change in order submissions by observing the timing of order entry, amendments, and deletions on one of the exchanges for which we have access to order data. Overall, our results indicate that adding a random auction ending time can reduce the risk of stock market manipulation and improve price efficiency.

Alternate closed-form weibit-based model for assessing travel choice with an oddball alternative

Herein, a weibit-based model is proposed as an alternative to Recker's logit choice model with an “oddball” alternative, which explicitly focuses on a single alternative that has unique attributes to other conventional alternatives in the choice set [Recker, W.W. (1995). Discrete choice with an oddball alternative. Transportation Research, 29B, 201–212]. While retaining the closed-form probability expression, the proposed model handles the oddball alternative using a multiplicative random disutility function assuming Weibull distributed random components. The proposed model thus allows disutility-dependent perception variances of both the conventional and oddball alternatives and a flexible variance ratio between them, which are effective to reflect the way how individuals perceive varying magnitudes of travel disutility from different attributes. This gives the proposed model more flexibility to consider various heterogeneity issues, including the heterogeneous perceptions of conventional alternatives, heterogeneous perceptions of unique and common attributes of the oddball alternative, and heterogeneous features of conventional and oddball alternatives. The empirical application of the proposed model is explored to highlight its practical performance. The results demonstrate the superiority of the proposed model in the choice contexts where both oddball effect and heterogeneity issues need to be considered. The proposed model could further provide new behavioral insights into various decision-making scenarios of transportation networks, such as transportation mode choices in the current era of emerging technologies and destination choices in urban agglomerations.

TESTING THE MARKET EFFICIENCY WHEN INTEREST RATES CHANGE: CASE IN INDONESIA

Until the end of September 2023, the interest rate policy in the Republic of Indonesia shifted from 3.50% to 5.75%. The objective of this study is to examine whether changes in interest rates have an impact on the market efficiency in Indonesia. The daily market returns of Indonesia Stock Exchange (IDX) indices from January 3rd, 2022, until October 9th, 2023 are employed. To examine the market efficiency in weak form, this study conducts the normality test by the Kolmogorov-Smirnov test, the unit root problem test by Augmented Dickey-Fuller test, and the variance ratio test. This study finds that most market indices experienced a decline in returns and were less volatile when interest rates shifted to higher levels. This study also finds that most market indices tend to remain efficient in weak form at both low and high interest rates. The finding implies that those indices tend not to be influenced by policy changes in interest rates. However, the findings also show that several market indices experience changes in conditions when interest rates shift. As the studies on the relationship between changes in interest rates and market efficiency are scarce, the novelty of this study is the use of event windows to get specific impact of changes in interest rates on market efficiency.

Limits of arbitrage and their impact on market efficiency: Evidence from China

This paper examines the impact of limits of arbitrage (LOA) on market efficiency by considering a large sample of Chinese stocks. Intraday market efficiency is measured using two widely used measures: the intraday return predictability measure and the variance ratio measure. We find that LOA plays a major role in driving market efficiency. We also use an exogenous shock, the introduction of Shenzhen Stock Connect, which increases trade volume and lowers LOA, to examine the impact of LOA on market efficiency. Our results indicate that this event improves market efficiency regarding both our measures. Therefore, we conclude that policy makers in China are acting in the right direction to elevate China's status in world markets by adapting policies that inherently make the country more attractive to global investors by lowering LOA and enhancing market efficiency.

Testing powers of the ratio of variances of two normal populations with a common mean

This article addresses the problem of hypothesis testing about the powers of the ratio of variances of two normal populations with a common mean. Different test procedures are proposed, such as the likelihood ratio test, the standardized likelihood ratio test, the parametric bootstrap likelihood ratio test, the computational approach test and its modification. Further, several generalized p-value approach test procedures are derived using some of the existing common mean estimators. The performances of all the suggested test methods are compared numerically in terms of their size values and power functions. In light of our simulation findings, we provide a few suggestions for utilizing the proposed test methods. Finally, we analyse real-life data to show the potential application of the proposed model.

Approbation of the Scale of Attitudes towards Intercultural Learning in Higher Education

The ability to cope with the challenges of cultural diversity is one of the key competencies that students need to develop in the contemporary world. This actualizes the question of intercultural learning and students' attitudes towards it. The study aimed at development and validation of the instrument to measure students’ attitudes towards intercultural learning. Taking into account the “sources” and processes of intercultural learning available to students, as well as the structure of the attitude, an instrument consisting of four scales were created - each of them includes three aspects of the attitudes: cognitive, affective and behavioral ones. The reliability and validity of each of the instrument were confirmed on a sample of 399 students of Russian universities using statistical procedures such as exploratory and confirmatory factor analysis, analysis of the consistency of the scales according to Cronbach's alpha and McDonald’s omega, analysis of extracted mean variance and heterotrait-monotrait ratio. It seems promising to consider various aspects of intercultural learning in further research, adapting and using the scales not only in the higher education system, but also in other contexts and age groups.

143 Validation Strategies of Sensor Data in the Context of Heat Stress Detection

Abstract Evaluating genetically heat stress (HS) of cattle is still a major challenge, also because of the need to have access to HS sensitive phenotypes relating their reaction to temperature and humidity as described by the temperature-humidity index (THI). A solution could be to add the information of data from sensors. However, activity (ACT) and rumination (RUM) sensors reflect no “production” [i.e., milk yields (MY), milk composition, but also intake or growth] related aspects which is suboptimal. Therefore, the objectives of this study were thus to assess the possible usefulness for adding sensors data for HS genetic evaluation based on a dairy situation. But the context described can be easily enlarged and include beef cattle and pigs. Strategy was illustrated using daily SenseHub collar records that were obtained from October 2019 to July 2022 in six dairy herds in Wallonia in Southern Belgium. A total of 453 Walloon Holstein cows were followed during this period for activity time. Meteorological data and a HS sensitive “production” trait (here MY) were also obtained from 2015 to 2022 for 1,740 cows from the same herds. In total 32,154 MY, 130,867 ACT and 130,848 RUM records were available. The thresholds at which the different traits start to be affected by HS were estimated at a THI of 63, 64 and 66, respectively, for MY, ACT and RUM. A three-trait random regression reaction norm model was fitted with these different thresholds. Estimated heritability values were 0.19 ± 0.03, 0.14 ± 0.06 and 0.21 ± 0.05 respectively for MY, ACT and RUM using AIREML. Ratios of variance associated to THI and constant genetic effect were 0.002, 0.02 and 0.04 indicating a stronger reaction by RUM but also ACT than MY to THI. However, it is uncertain if the reactions of these sensor traits are reflected in the production traits. Estimated genetic correlations of regressions on THI for ACT and RUM showed values of 0.51 ± 0.70 and 0.08 ± 0.54 with MY and 0.77 ± 0.69 between ACT and RUM. The first eigenvector of the correlation matrix explained 65% of the total variability and standardized coefficients of this eigenvector were 0.42, 0.69 and 0.59 for MY, ACT and RUM. A total of 50% of the variance associated with the regression on THI for MY could be explained by the regressions on THI for ACT and RUM. Adding the constant genetic effects for ACT and RUM only marginally increased to 51% the ability to explain the effect of THI on MY. Based on these results, reactions of different indicator traits, here sensor data, may reflect a different reaction than production and therefore economically important traits. Additional research, also beyond dairy cattle, should continue to address this topic that is very important for the validation of sensor data detecting HS.

Mixed Correlation Coefficient Between Probability Hesitation Fuzzy Sets and Applications

Probability hesitation fuzzy sets(PHFSs) have been paid increasing attention in the fuzzy domain nowadays, and correlation coefficient is becoming an important research content in fuzzy data analysis, many scholars have been conducted relevant researches on it. However, the existing correlation coefficients between PHFSs have some limitations, such as not considering the number of membership degrees and having counter-intuitive phenomenon to some extent. Therefore, we propose the mixed correlation coefficient between PHFSs. To begin with, we give the concepts of the average, variance, and length ratio of PHFE to illustrate the integrity, distribution, and length. Then, we define the average, variance, and length three correlation coefficients respectively on the above basic concepts. Furthermore, we construct the mixed correlation coefficient through combining these basic correlation coefficients, and extend to weighted form in addition, which addresses the issues of the available correlation coefficients. Finally, we utilize proposed correlation coefficient to analysis problems of data association and decision making. The effectiveness and rationality of the proposed method is illustrated at length.

Variability analysis of muscle activation symmetry to identify indicators of individual motor strategy: a case series on elite Paralympic powerlifters.

In Paralympic powerlifting competitions, movement execution symmetry is a technical requirement influenced by individual athlete characteristics and motor strategies. Identifying the elements associated with individual motor strategies can offer valuable insight for improving sport performance. Therefore, this case series study aimed to explore muscle activation symmetry and its intra- and inter-individual variability to determine the muscles mostly related to individual motor strategies in elite Paralympic powerlifters. Bilateral electromyographic activation of the anterior deltoid (AD), pectoralis major (PM), latissimus dorsi (LD), triceps (TRI) and external oblique (EO) muscles were analysed in five elite Paralympic powerlifters while performing four sets of one-repetition maximum of Paralympic bench press. Muscle activation symmetry indexes (SI) were obtained and transformed to consider individual-independent evaluation. The coefficient of variation (CV), variance ratio (VR), and mean deviation (MD) were computed to assess inter- and intra-individual variability in electromyographic waveforms and SI. Both transformed and non-transformed SI indicated overall symmetric activation in DA, PM, TRI, and LD. Transformed SI revealed asymmetrical muscle activation of EO when grouping data (mean bilateral difference: 10%). Athletes exhibited low intra-individual SI variability in all analysed muscles (CV < 10%) and low inter-individual variability in DA, PM, LD, and TRI (CV < 10%; VR: 4%-11%; MD: 29%-43%). In contrast, higher inter-individual variability was observed in EO (CV: 23%; VR: 23%; MD: 72%-81%). The highest variability and asymmetry in abdominal muscle activation among athletes emphasize the importance of personalized training approaches for targeting these muscles due to their role in individualizing motor strategies.

Dose reduction does not impact the precision of CT-based RSA in tibial implants: a diagnostic accuracy study on precision in a porcine cadaver

Background and purpose: Radiostereometric analysis (RSA) is the gold standard for evaluation of migration of implants. CT-RSA has been shown to have precision at the level of RSA in hip, shoulder, and knee joint replacements. We aimed to assess the impact of dose reduction on precision of CT-RSA on tibial implants, comparing it with previously published data on precision of standard dose CT-RSA on tibial implants.Material and methods: We performed a total knee arthroplasty on a porcine knee cadaver, and subsequent CT-RSA with low effective doses (0.02 mSv). We compared the results with previously published CT-RSA data with standard (0.08 mSv) dose. The primary outcome variable was the difference in precision of the maximum total translation (MTT). Secondary variables included ratios of variances and standard deviations, and precision of peripheral point translations, center-of-mass translations, and rotations. A difference of more than 0.1 mm in precision was defined as clinically relevant. Our hypothesis was that precisions of low and standard CT-RSA doses were equal.Results: Low dose (mean 0.07, 95% confidence interval [CI] 0.06–0.08) and standard dose CT-RSA (0.08, CI 0.07–0.09) achieve similar precision, with difference in precision of MTT of 0.01, CI 0.00–0.02 mm. The F-statistic (0.99, CI 0.63–1.55) and sdtest (1.05, CI 0.43–2.58) also supported this.Conclusion: We conclude that the precision of low dose CT-RSA for tibial implants on a porcine cadaver is equal to standard dose CT-RSA. However, these findings should be confirmed in clinical trials.

Estimation of stability index for symmetric $$\alpha $$-stable distribution using quantile conditional variance ratios

AbstractThe class of $$\alpha $$ α -stable distributions is widely used in various applications, especially for modeling heavy-tailed data. Although the $$\alpha $$ α -stable distributions have been used in practice for many years, new methods for identification, testing, and estimation are still being refined and new approaches are being proposed. The constant development of new statistical methods is related to the low efficiency of existing algorithms, especially when the underlying sample is small or the distribution is close to Gaussian. In this paper, we propose a new estimation algorithm for the stability index, for samples from the symmetric $$\alpha $$ α -stable distribution. The proposed approach is based on a quantile conditional variance ratio. We study the statistical properties of the proposed estimation procedure and show empirically that our methodology often outperforms other commonly used estimation algorithms. Moreover, we show that our statistic extracts unique sample characteristics that can be combined with other methods to refine existing methodologies via ensemble methods. Although our focus is set on the symmetric $$\alpha $$ α -stable case, we demonstrate that the considered statistic is insensitive to the skewness parameter change, so our method could be also used in a more generic framework. For completeness, we also show how to apply our method to real data linked to financial market and plasma physics.

Doppler effect and Rossby waves in the ocean: A brief history and new approaches

The review is devoted to Rossby waves in the ocean. Currently, there are many monographs and scientific articles on this topic, in which the authors approach the presentation of the material in different ways. For researchers who have not delved too deeply into this topic, the analysis of these sources is often perceived as a collection of disparate and often contradictory information that does not allow an adequate understanding of the subject. The review is based on the analysis of the main publications on this topic, and it systematizes the main ideas in various aspects. We also give the readers a comparison of different approaches in this area. Particular attention is paid to the review of the dispersion relations of Rossby waves in the presence of a background flow with an emphasis on the presence or absence of a Doppler additive to the frequency. Although the problem statements and variance ratios under consideration are generally well-known, however, they are presented in significantly different ways by many authors, which often leads to misunderstanding and confusion. We draw the reader’s attention to the key controversial points and bring various approaches into a single coherent system. If long Rossby waves do not “feel” the flow, then this is true for the “shallow water” model and is a consequence of the Galilean non-invariance of the dispersion relation. Considering various approaches, we show that there is no strict dispersion relation for the Galilean-non-invariant dispersion relation. Some not quite strict assumptions and assumptions are always added, such as the formal existence of vertical boundaries or the dependence of the barotropic radius on the variable transverse coordinate. The derivation of the dispersion relation with the Doppler shift also contains some asymptotic expansions, accompanied by an analysis of the theory of dimensions. Using common terminology, we combine the main analytical results on the topic and present them in a single logic.

Optimization of viscoelastic behaviors of bioinspired asymmetric helicoidal CFRP composites using Taguchi Method

The dynamic mechanical properties play an important role in the selection of suitable materials in the manufacturing wing of aircraft and wind turbine blades. In this paper, the standard Taguchi method was used to examine the effect of inter-ply stacking angles of 0° (UD), 0/90° (cross-ply), 5°, 15°, 10°, 20°, 25° 30° and aging temperature (ambient temperature, 40o, 60o) on the dynamic mechanical properties of bioinspired asymmetric helicoidal Carbon Fiber Reinforced Plastic (CFRP) composites. The standard Taguchi’s L18 was used. The signal-to-noise ratio and analysis of variance were introduced to analyze and estimate the optimal combination parameters. The results show the dynamic mechanical properties are linearly correlated to the fiber architecture and aging temperature. Analysis of variance (ANOVA) indicates that inter-ply stacking angles (15°, and 20°) and aging temperature (40o, 60o) are the main significant factors affecting the dynamic mechanical values at a 95% confidence level. Inter-ply stacking angles are finally noted as critical factors affecting the extent of macromolecular mobility within helicoidally stacked continuous fiber CFRP composites. A confirmation test validated the optimized results and it was found that there were improvements in S/N ratios from initial to optimal setting. The experimental and expected results are very close, with an error ratio not exceeding 5%.

POLYNOMIAL ESTIMATION OF DATA MODEL PARAMETERS WITH NEGATIVE KURTOSIS

Context. The paper focuses on the problem of estimating the center of distribution of the random component of experimental data for density models with a negative kurtosis.&#x0D; Objective. The goal of this research is to develop methods to improve the efficiency of polynomial estimation of parameters of experimental data with a negative kurtosis coefficient.&#x0D; Method. The study applies a relatively new approach to obtaining estimates for the center of the probability distribution from the results of experimental data with a stochastic component. This approach is based on polynomial estimation methods that rely on the mathematical apparatus of Kunchenko's stochastic polynomials and the description of random variables by higher-order statistics (moments or cumulants). A number of probability density distributions with a negative kurtosis coefficient are used as models of the random component.&#x0D; As a measure of efficiency, the ratio of variance of the estimates for the center of the distribution found using polynomial and classical methods based on the parameter of amount of information obtained is used.&#x0D; The relative accuracy of polynomial estimates in comparison with the estimates of the mean, median and quantile estimates (center of curvature) is researched using the Monte Carlo method for multiple tests.&#x0D; Results. Polynomial methods for estimating the distribution center parameter for data models of probability distribution density with a negative kurtosis coefficient have been constructed.&#x0D; Conclusions. The research carried out in this paper confirms the potentially high efficiency of polynomial estimates of the coordinates of the center of the experimental data, which are adequately described by model distributions with a negative kurtosis. Statistical modeling has confirmed the effectiveness of the obtained estimates in comparison with the known non-parametric estimates based on the statistics of the mean, median, and quantile, even with small sample sizes.

Single Objective Optimization of Cutting Parameters for Surface Roughness in Turning of Inconel 718 Using Taguchi Approach

The majority of work in cutting machining processes is focused on choosing the parameters that will result in the greatest rate of material removal and the least amount of surface roughness, cutting temperatures, cutting pressures, vibrations, etc., which are the main quality responses. Surface roughness is one of the most precise quality criteria that affects how machined parts work. By choosing the appropriate cutting settings, it should be possible to get a greater surface finish and a longer service life for the machined parts. The link between changes in surface roughness caused by turning operations with respect to different machining settings is investigated in this study using the Taguchi method L9(33). The orthogonal array, signal-to-noise ratio, and analysis of variance are utilized to examine the performance characteristics when turning Inconel 718 bars with CCMT09T308N-SU coated cemented carbide insert tools. The optimal setting of cutting parameters to lessen surface roughness is chosen using the Taguchi method. Speed, feed rate, and cut depth are the three cutting parameters. Experimental results are given to illustrate the effectiveness of this strategy.

Ecological Niche and Interspecific Association of the Main Fishes in the Coastal Waters of Hainan Island, China

This study explored the ecological niche and interspecific relationships among the main fish species in the coastal waters of Hainan Island based on data from fishery stock surveys conducted in the spring and autumn of 2022. The methods of chi-square test, percentage of co-occurrence (PC), association coefficient (AC), cluster analysis, and redundancy analysis were used to analyze the interspecific associations and influence of environmental factors on the ecological niches of fish communities. According to the cluster analysis of niche breadth, 20 main fishes could be divided into broad, medium, and narrow niche species. There were four and eight broad niche species in spring and autumn, respectively. The ranges of niche overlap values were 0.001–0.91 in spring and 0–0.87 in autumn, indicating that the species differed and were similar in their ability to utilize resources, survive in habitats, and prey. According to the variance ratio and statistic value W, the main fishes in spring showed a significant positive association, whereas those in autumn showed a positive association, but not at a significant level, indicating that the main fishes in spring were more closely associated with each other. There were 56 species pairs in the 2 seasons that were significantly associated (χ2 ≥ 3.841). AC and PC tests revealed that the interspecific association was strong and tended to be positive. According to the redundancy analysis, environmental factors such as surface temperature, water depth, and pH significantly affected the main fishes in spring, while environmental factors such as dissolved oxygen, bottom temperature, surface salinity, and pH significantly affected those in autumn.

Impact of Tax Implementation on Fintech P2P Loans in Indonesia

This research paper aims to examine the impact of tax implementation on the number of P2P loan recipients and the amount of P2P loan disbursement in fintech industry of Indonesia. This empirical study is based on the number of accounts and loan data acquired from one of Indonesia’s government agencies – the Financial Services Authority (OJK) from February 2022 to April 2022 and June 2022 to August 2022 that are analyzed using various tests such as Skewness-Kurtosis Test, the variance ratio test, and t-test. The results show that tax implementation does not significantly affect the number of P2P loan recipients and the amount of P2P loan disbursement. This is because fintech offers greater benefits than traditional banks, such as convenience, time-saving, more access to financial products, and better security measures. The limited amount of available data and the number of provinces available become the limitation of the study to obtain optimum results.

Nonequilibrium Effects on the Precision of Parameter Estimation

AbstractThe impact of nonequilibrium environment effects on the accuracy of quantum parameter estimation is investigated, and it is found that these effects can significantly affect estimation accuracy. Using an individual estimation strategy reveals that the nonequilibrium effects consistently enhance accuracy, regardless of the coupling strength between the probe and its environment. In contrast, weak memory effects undermine estimation accuracy. When employing a multi‐parameter simultaneous estimation strategy, it is observed that the nonequilibrium effects consistently improve the advantages of simultaneous estimation, as analyzed by the ratio of total variances between the two estimation scenarios. However, the memory effects on these advantages depend on the coupling strength between the qubit and the environment. These findings suggest that appropriate parameters of a nonequilibrium environment can increase the quantum Fisher information (QFI), thereby enhancing the accuracy of quantum parameter estimation. These significant results are essential for improving parameter estimation accuracy in quantum systems interacting with nonequilibrium environments.