Nonparametric Measures Research Articles

Insights into Stable Apple Genotypes for Fruit Yield in Himachal Pradesh: An Assessment Using Parametric and Non-parametric Stability Measures

Insights into Stable Apple Genotypes for Fruit Yield in Himachal Pradesh: An Assessment Using Parametric and Non-parametric Stability Measures

Investigating the price determinants of the European Emission Trading System: a non-parametric approach

Understanding the intricacies of factors influencing European Union Emission Trading System (EU ETS) market prices is paramount for effective policy making and strategy implementation. We propose the use of the Information Imbalance, a non-parametric measure recently introduced in the physics community for quantifying the degree to which a set of variables is informative with respect to another one, to study the relationships among macroeconomic, economic, uncertainty, and energy variables concerning EU ETS price between January 2014 and April 2023. Our analysis shows that in Phase 3, commodity-related variables such as the ERIX index are the most informative in explaining the behaviour of the EU ETS market price. Transitioning to Phase 4, financial fluctuations take centre stage, with the uncertainty in the EUR/CHF exchange rate emerging as a crucial determinant. These results reflect the disruptive impacts of the COVID-19 pandemic and the energy crisis in reshaping the importance of the different variables. In addition to highlighting the shift in influential factors between Phase 3 and Phase 4, our findings underscore how macroeconomic volatility and energy disruptions have altered market dynamics. Notably, during the COVID-19 pandemic, the volatility in financial markets and fluctuations in energy demand and supply significantly affected the predictive power of different variables. Moreover, the energy crisis amplified the sensitivity of EU ETS prices to energy-related factors, reinforcing the importance of incorporating multiple dimensions into market analysis. Beyond variable analysis, we also propose to leverage the Information Imbalance to address the problem of mixed-frequency forecasting, and we identify the weekly time scale as the most informative for predicting the EU ETS price. Finally, we show how the Information Imbalance can be effectively combined with Gaussian Process regression for efficient nowcasting and forecasting using very small sets of highly informative predictors.

Poisson’s ratio-LambdaRho rock-physics templates and a study on sensitivity of different fluid indicators

Seismic fluid indicators are highly accurate when calibrated, but when the data is scarce, an interpreter must choose between different indicators. We investigate the data from multiple basins to understand the most effective fluid indicators for use. Unlike previous studies, the data comprises a large, equal, and statistically meaningful number of hydrocarbon and brine sands from different basins. We show that Poisson’s ratio-LambdaRho templates can be used to separate different facies in synthetic and real data and can be used as a useful crossplot interpretation tool. We develop a fluid indicator, as LambdaRho Poisson’s ratio multiplication [Formula: see text], which is highly sensitive to saturation and can be potentially used as a fizz-gas discriminator. We compare the sensitivity of different fluid indicators to hydrocarbon saturation by using Bhattacharyya distance, which provides a quantitative metric for how well different indicators separate hydrocarbon and brine sands, and it is a nonparametric measure unlike other fluid indicator scores developed in similar studies. Absolute properties derived from seismic by inversion are rarely available in regional studies, whereas relative elastic properties can be easily obtained and used. Following the concepts of elastic reflectivity vectors and geometry of intercept-gradient crossplots, we show how the reflectivity of different fluid indicators can be approximated from amplitude variation with offset (AVO) parameters at various chi ([Formula: see text]) angles, enabling an interpreter to use them even when inversion products are not available. Finally, we compare the effectiveness of relative elastic parameters on different AVO classes and show that no single attribute works best across all classes but for general screening purposes fluid factor and [Formula: see text] can be good choices. The findings of this study can help better characterization of fluids in exploration, appraisal, and development of hydrocarbons, and in other areas where monitoring produced and injected fluids is important like 4D seismic or carbon capture storage.

A Survey of Pain and Musculoskeletal Dysfunction Prevalence After Gender-Confirming Surgery of the Urogenital System

Purpose: We sought to (1) explore the prevalence of pain, and movement and urogenital dysfunction reported following gender confirming vaginoplasty (V) and phalloplasty (P), (2) identify which providers were consulted for pain, and movement and urogenital dysfunction after surgery, and (3) compare these factors between people receiving V and P surgeries. Methods: A custom internet survey, built in REDCap, was distributed through LGBTQIA+ organizations across the US. The survey collected demographic information, types of surgery, postsurgical impairments (pain and urogenital dysfunction), and activity limitations, along with the types of providers seen and interventions provided. Summary statics were calculated and proportions or means and standard deviations based on the data structure. Nonparametric measures were used to test associations between postsurgical care, gender identity, and geographic location. Results: 584 responses remained after data cleaning of which 89 people reported having vaginoplasty (V) and 118 had phalloplasty (P). The average age of respondents was 28.6 ± 5.2 years. 70% of respondents reported pain, 25% difficulty moving, 23% bowel or bladder dysfunction, and 9% dyspareunia. Significantly more respondents who had V reported dyspareunia, while more respondents who had P reported incontinence. 20%, 29%, 15%, and 13% of included respondents received care from a physical therapist for pain, difficulty moving, incontinence, and dyspareunia, respectively. Discussion: These results indicate that both individuals who undergo V or P procedures report musculoskeletal pain, movement problems, and pelvic floor dysfunction following GCS. Notably, these issues are commonly addressed in cisgender patients by physical rehabilitation providers. However, less than half of our sample were referred to a physical therapist.

Food insecurity among students in Open Distance and e-Learning in South Africa

Food insecurity is a widely studied phenomenon; however, studies documenting food insecurity among Open Distance and e-Learning students are sadly lacking. This paper aims to study the prevalence of food insecurity among Open Distance and e-Learning students in South Africa. The purpose is to test the common assumption that Open Distance and e-Learning students do not struggle with food insecurity as they are typically living at home or employed. The method used in this paper was an online anonymous version of the Food Insecurity Experience Scale and was administered through Qualtrics. Only 27.9% (n=2084) of respondents were food secure and mildly food insecure (score of 1 to 4), while those who were moderately food insecure constituted 16.7% (n=1 250) of the sample (score of 5 to 6) and those with severe food insecurity constituted 55% (n= 4 130). The dependent variable was not normally distributed and therefore nonparametric measures were used to test for differences in groups, namely, the Kruskal Wallis and the Mann-Whitney U tests. The results show that African students are more likely to experience food insecurity compared to their counterparts, while there were no substantive differences in gender. Members of the LGBTQI community were also shown to be at higher risk of food insecurity. Those whose primary income was either grants or income from an informal business were at higher risk of food insecurity than those who worked full time. The findings of this study underscore the pervasive nature of food insecurity among students in South African Open, Distance and e-Learning education

How many days are enough? Sleep-wake timing regularity and fragmentation scores change with the number of days included.

The duration of sleep data collection from actigraphy is often influenced by practical factors (e.g. workdays versus non-workdays), but the impact of the variation of duration on outcome measures of interest has not been well explored. This study investigates the effect of the duration of actigraphy measurement on non-parametric measures of 24-hr sleep-wake rhythms. We examined regularity inter-daily stability and fragmentation intra-daily variation over 14 days or the first 7 days in participants (n = 41) undergoing evaluation for sleep disorders. Bland-Altman plots assessed the impact of fewer than 14 or 7 days, respectively, on inter-daily stability and intra-daily variation scores. Intra-daily variation values were also calculated for each day and compared with the 14-day intra-daily variation. Compared with the entire 14-day period, using shorter durations (< 7 days) led to a higher estimated bias and increased variance in the limits of agreement for inter-daily stability. Intra-daily variation values showed increased variation in the limits of agreement with fewer days. Similar trends were observed when comparing shorter actigraphy periods 3 or 5 days-7 days. Daily intra-daily variation calculations indicate that individuals with higher daily fragmentation experienced more pronounced day-to-day fragmentation and greater variability in the degree of fragmentation, in a linear association between daily intra-daily variation standard deviation and 14-day intra-daily variation values. Our data indicate that a minimum of 7 full days of actigraphy is recommended to reduce measurement errors, and intra-daily variation and inter-daily stability derived from less than 7 days cannot be compared with those from more than 7 days without significant error.

A robust non-parametric stability measure to select stable genotypes

A robust non-parametric stability measure to select stable genotypes

From Radar Sensor to Floating Car Data: Evaluating Speed Distribution Heterogeneity on Rural Road Segments Using Non-Parametric Similarity Measures

Rural roads, often characterized by winding paths and nearby settlements, feature frequent curvature changes, junctions, and closely spaced private accesses that lead to significant speed variations. These variations are typically represented by average speed or v85 profiles. This paper examines complete speed distributions along rural two-lane roads using Floating Car Data (FCD). The Wasserstein distance, a non-parametric similarity measure, is employed to compare speed distributions recorded by a radar Control Unit (CU) and a selected FCD sample. Initially, FCD speeds were validated against CU speeds. Subsequently, differences in speed distributions between the CU location and specific sections identified by sharp curves, intersections, or accesses have been assessed. The Wasserstein Distance is proposed as the most effective synthetic indicator of speed distribution variability along roadways, attributed to its metric properties. This measure offers a more concise and immediate assessment compared to an extensive array of statistical metrics, such as mean, median, mode, variance, percentiles, v85, interquartile range, kurtosis, and symmetry, as well as qualitative assessments derived from box plot trends.

A morphological analysis of the galaxy cluster XLSSC 122 at z=1.98

Abstract We present a morphological analysis of 29 spectroscopically confirmed members of XLSSC 122, a massive galaxy cluster at z = 1.98. We perform photometry using Statmorph on images of the cluster members from the Hubble Space Telescope (HST) Wide Field Camera (WFC3) in the F140W band. We visually assess the images and compute non-parametric morphological measures, namely the concentration C, asymmetry A, Gini and M20 values and use them to classify cluster members as either being bulge-dominated, disk-dominated or presenting possible merger features. The morphological properties of the XLSSC 122 members show clear evidence of bimodality. The bulge-dominated galaxies are redder, older and are found in the denser regions of the cluster, while the galaxies showing disturbed features are bluer, younger and are found towards the outskirts of the cluster. XLSSC 122 is also found to be deficient in blue and disturbed galaxies compared to field galaxy populations from the CANDELS/3D-HST surveys. An analysis of merger events occurring in numerical simulations suggest that galaxy interactions generating a population of morphologically disturbed galaxies in XLSSC 122 may have occurred over the interval 2 &amp;lt; z &amp;lt; 3, i.e. prior to their infall into the virial core of the cluster.

A nonparametric entropy-based measure of mass political polarization

A nonparametric entropy-based measure of mass political polarization

A nonparametric measure of contrast in x-ray images

Objective. We propose a nonparametric figure of merit, the contrast equivalent distance CED, to measure contrast directly from clinical images. Approach. A relative brightness distance δ is calculated by making use of the order statistic of the pixel values. By multiplying δ with the grey value range R, the mean brightness distance MBD is obtained. From the MBD, the CED and the distance-to-noise ratio DNR can be derived. The latter is the ratio of the MBD and a previously suggested nonparametric measure τ for the noise.Since the order statistic is independent of the spatial arrangement of the pixel values, the measures can be obtained directly from clinical images. We apply the new measures to mammography images of an anthropomorphic phantom and of a phantom with a step wedge as well as to CT images of a head phantom. Main results. For low-noise images of a step wedge, the MBD is equivalent to the conventional grey value distance. While this measure permits the evaluation of clinical images, it is sensitive to noise. Therefore, noise has to be quantified at the same time. When the ratio σ/τ of the noise standard deviation σ to τ is available, validity limits for the CED as a measure of contrast can be established. The new figures of merit can be calculated for entire images as well as on regions of interest (ROI) with an edge length not smaller than 32 px.Significance. The new figures of merit are suited to quantify the quality of clinical images without relying on the assumption of a linear, shift-invariant system. They can be used for any kind of greyscale image, provided the ratio σ/τ can be estimated. This will hopefully help to achieve the optimisation of image quality vs dose required by radioprotection laws.

Do galaxy mergers prefer under-dense environments?

Context. Galaxy mergers play a crucial role in galaxy evolution. However, the correlation between mergers and the local environment of galaxies is not fully understood. Aims. We aim to address the question of whether galaxy mergers prefer denser or less dense environments by quantifying the spatial clustering of mergers and non-mergers. We use two different indicators to classify mergers and non-mergers – classification based on a deep learning technique (f) and non-parametric measures of galaxy morphology, Gini-M20 (g). Methods. We used a set of galaxy samples in the redshift range 0.1 &lt; z &lt; 0.15 from the Galaxy and Mass Assembly (GAMA) survey with a stellar mass cut of log(M⋆/M⊙) &gt; 9.5. We measured and compared the two-point correlation function (2pCF) of the mergers and non-mergers classified using the two merger indicators f and g. We measured the marked correlation function (MCF), in which the galaxies were weighted by f to probe the environmental dependence of galaxy mergers. Results. We do not observe a statistically significant difference between the clustering strengths of mergers and non-mergers obtained using 2pCF. However, using the MCF measurements with f as a mark, we observe an anti-correlation between the likelihood of a galaxy being a merger and its environment. Our results emphasise the advantage of MCF over 2pCF in probing the environmental correlations. Conclusions. Based on the MCF measurements, we conclude that the galaxy mergers prefer to occur in the under-dense environments on scales &gt; 50 h−1 kpc of the large-scale structure (LSS). We attribute this observation to the high relative velocities of galaxies in the densest environments that prevent them from merging.

Exploring Resistant Sources of Chickpea against Fusarium oxysporum f. sp. ciceris in Dryland Areas

Fusarium wilt is a fungal disease that has a significant impact on chickpeas worldwide. This study examined the response of 58 chickpea genotypes to Fusarium wilt. The experiment was conducted over two growing seasons at the Sararoud and Maragheh research stations at the Drylands Agricultural Research Institute of Iran. Genotype resistance was screened through wilt incidence records and nonparametric stability statistic evaluation. The identified resistant genotypes were then evaluated in the greenhouse for their response to four isolates of Fusarium oxysporum f. sp. ciceris (races 1/BC, 2, 4, and 6). Out of 58 genotypes, 32 exhibited moderate resistance, while 24 showed strong resistance abilities. Under warmer conditions, disease severity was higher, with scores at the Sararoud location being higher than those at the Maragheh location. Of the total genotypes across all locations and years, 41.4% were resistant, 55.17% were moderately resistant, 1.72% were susceptible, and 1.72% were highly susceptible. The nonparametric stability measures S(1), S(2), and S(3) identified FLIP 05-42C and FLIP 05-43C as stable and resistant genotypes. The study found that Azad/Hashem K3 was stable based on the non-parametric stability measure S(6). Other resistant genotypes were identified using stability parameters NP(1), NP(3), and NP(4), while FLIP 05-104C was identified by NP(2). The genotypes selected by nonparametric stability parameters showed resistance against at least two Fusarium oxysporum f. sp. ciceris races. The screening method and nonparametric stability statistics used in this study were effective in identifying sources of resistance to Fusarium oxysporum f. sp. ciceris.

Identification of miR-125a and miR-106b signature as a potential diagnostic biomarker in breast cancer tissues

MicroRNAs (miRNAs) have essential roles in the etiology of breast cancer and are regarded as possible markers in this malignancy. In order to find new markers for breast cancer, the current study has measured expression level of four miRNAs, namely miR-125a, miR-106b, miR-96 and miR-92a-3p in the paired breast samples. Expression levels of miR-125a and miR-106b were higher in tumoral tissues compared with control tissues (Expression ratios (95% CI) = 4.01 (1.96–8.19) and 3.9 (1.95–7.81); P values = 0.0005 and 0.0003, respectively). miR-106b and miR-125a differentiated between malignant and non-malignant tissues with AUC values of 0.7 and 0.67, respectively. We detected association between expression of miR-106b and clinical stage (P = 0.03), in a way that its expression was the lowest in the advanced stages. Finally, significant relationships were found between miR-96 and miR-125a in both tumoral and non-tumoral specimens (ρ = 0.76 and 0.69, respectively). This nonparametric measure of rank correlation also showed relationship between miR-106b and miR-96 in both sets of samples (ρ = 0.63 and 0.61, respectively). Cumulatively, the assessed miRNAs, particularly miR-125a and miR-106b are putative targets for further expression and functional assays in breast cancer.

A guide to measuring expert performance in forensic pattern matching

Decisions in forensic science are often binary. A firearms expert must decide whether a bullet was fired from a particular gun or not. A face comparison expert must decide whether a photograph matches a suspect or not. A fingerprint examiner must decide whether a crime scene fingerprint belongs to a suspect or not. Researchers who study these decisions have therefore quantified expert performance using measurement models derived largely from signal detection theory. Here we demonstrate that the design and measurement choices researchers make can have a dramatic effect on the conclusions drawn about the performance of forensic examiners. We introduce several performance models – proportion correct, diagnosticity ratio, and parametric and non-parametric signal detection measures – and apply them to forensic decisions. We use data from expert and novice fingerprint comparison decisions along with a resampling method to demonstrate how experimental results can change as a function of the task, case materials, and measurement model chosen. We also graphically show how response bias, prevalence, inconclusive responses, floor and ceiling effects, case sampling, and number of trials might affect one’s interpretation of expert performance in forensics. Finally, we discuss several considerations for experimental and diagnostic accuracy studies: (1) include an equal number of same-source and different-source trials; (2) record inconclusive responses separately from forced choices; (3) include a control comparison group; (4) counterbalance or randomly sample trials for each participant; and (5) present as many trials to participants as is practical.

A comprehensive study on non-governmental actors in shaping grassland ecological compensation within legal frameworks

Ecological compensation has emerged as a crucial institutional framework for managing the interplay between ecological preservation and economic development in China. This study focuses on the specific case of grassland ecological compensation to investigate the protection of rights and interests of non-governmental subjects. By utilizing data derived from questionnaire responses, this study examines the legal rights, obligations, and responsibilities associated with grassland ecological compensation. Statistical techniques such as Z-distribution, chi-square test, and non-parametric measures of correlation are employed to analyze the collected data, which are presented using tables and graphs. Furthermore, this research evaluates the current state of rights and interests of compensation subjects engaged in ecological compensation practices, aiming to enhance our comprehension and assessment of the extent to which the ecological compensation system safeguards the rights and interests of individuals. The findings show that a substantial number of respondents see current grassland ecological compensation methods in China as reasonable but insufficient, indicating a need for method diversification. There’s a clear preference for a shared responsibility model over government-only funding, especially in regions with large grassland areas. This highlights the necessity for adaptable laws and a legal framework that accommodates diverse stakeholder needs. Additionally, the importance of clear property rights is emphasized for sustainable land use. The study suggests legislative reform towards a more equitable and effective approach to grassland conservation, providing valuable recommendations for refining and advancing the ecological compensation system.Author name 1 (Ziqi Liu) mismatch between ms and metadata. We have foolowed metadata. Kindly check and confirm.The metadata is right. Thank you.

Parametric and Non-Parametric Measures to Identify Stable and Adaptable Cotton (Gossypium Hirsutum L.) Genotypes

ABSTRACT The study, comprised seventeen genotypes, was conducted during 2016 to 2019 growing seasons. The design was Randomized Complete Block Design (RCBD) with three replications to identify adaptable cotton genotypes. Parametric and non-parametric measures, principal component analysis (PCA) and correlation among the ranks of the parameters computed using R software. The environment, genotype and genotype-environment interaction contributed 79.58, 3.2 and 15.46% of the variation, respectively, and were significant (p < 0.001). The highest (1510.7 kg/ha) and lowest (1080.1 kg/ha) seed cotton yield was recorded from G12 and G8 genotypes respectively. Coefficients of determination (R2) and superiority index (Pi) recognized G13, G11, G10 and G11, G12, G7 as the top three stable genotypes correspondingly. G10 was selected three times as superior by stability variance (σ2), wricke’s ecovalence (Wi) and deviation from regression (S2di). Seed cotton yield positively correlated with GAI, Kang’s rank-sum (KRS), Huhn and Nassar S(1), S(6) S(3) while negatively correlated with Thennarasu stability measures NP(2), NP(3) and NP(4 . The first, second and third clusters of the PCA biplot comprised, 4, 4 and 10 parameters respectively. G12, with highest seed cotton yield and good stability, was the best genotype and recommended for variety verification.

Unsupervised damage assessment under varying ambient temperature based on an adjusted artificial neural network and new multivariate covariance-based distances

Temperature variability is one of the critical environmental conditions that causes confusing changes in structural properties and dynamic responses of bridges similar to damage. In this case, false alarms and mis-detection are among the major errors in health monitoring of such civil structures. High damage detectability is another significant challenge in bridge health monitoring. To deal with these issues, this article proposes an unsupervised damage assessment technique comprising two steps of data normalization and novelty detection. For the first step, an adjusted artificial neural network is considered to remove the effects of temperature variability from dynamic features (modal frequencies). This process is carried out by an auto-associative neural network by adjusting its hidden layer neurons through a new hyperparameter selection algorithm. Using normalized features obtained from the first step, this article proposes three multivariate covariance-based distances called linear dissimilarity analysis, multivariate Kullback–Leibler divergence, and multivariate Bregman distance to compute damage indices or novelty scores for damage assessment. The fundamental principles of these distances lie in three aspects: dividing the normalized features into segments, estimating the covariances of segmented feature sets, and incorporating the estimated covariances into the proposed distance measures. The major contributions of this article include proposing three non-parametric distance measures and developing an unsupervised data normalization framework via a new hyperparameter tuning algorithm for adjusting an artificial neural network. A concrete box-girder bridge is considered to verify the proposed approach, along with several comparative studies. Results show that the method presented here can mitigate severe temperature variability and increase damage detectability with superiority over some traditional and state-of-the-art damage assessment techniques.

The Role of Modern Interactive Media in Making Travel Decisions

Interactive media play a significant role in making tourism travel decisions by providing information, opinions, and preferences to a large group of users of these media, which in turn crystallize the decision-making process at its various stages, whether before, during , or after the tourism trip . The research community identified the administrative leaders working in the tourism authority from the level of a responsible department upwards to the rank of general manager, who was selected as part of the study sample. The importance of the research lies in providing a philosophical basis for the nature of the researched variables based on the scarcity of studies linking the role of interactive media in making travel decisions. To achieve this, several main and sub-hypotheses were developed and tested using a set of non-parametric statistical measures, with a questionnaire used as a tool to collect data and information from the research community. In order to achieve the research goal, answer its questions, and test the validity of its hypotheses, the research relied on the questionnaire as the main tool for data collection and information, in addition to other methods such as personal interviews with managers and department heads at the tourism authority.

A Kernel Measure of Dissimilarity between M Distributions

Given M ≥ 2 distributions defined on a general measurable space, we introduce a nonparametric (kernel) measure of multi-sample dissimilarity (KMD) — a parameter that quantifies the difference between the M distributions. The population KMD, which takes values between 0 and 1, is 0 if and only if all the M distributions are the same, and 1 if and only if all the distributions are mutually singular. Moreover, KMD possesses many properties commonly associated with f-divergences such as the data processing inequality and invariance under bijective transformations. The sample estimate of KMD, based on independent observations from the M distributions, can be computed in near linear time (up to logarithmic factors) using k-nearest neighbor graphs (for k ≥ 1 fixed). We develop an easily implementable test for the equality of M distributions based on the sample KMD that is consistent against all alternatives where at least two distributions are not equal. We prove central limit theorems for the sample KMD, and provide a complete characterization of the asymptotic power of the test, as well as its detection threshold. The usefulness of our measure is demonstrated via real and synthetic data examples; our method is also implemented in an R package.