Ranked Set Research Articles

Diversity and Discrepancies in Water‐related University Rankings: Is There a Need for More Consistency or Is There Value in Breadth?

Diversity and Discrepancies in Water‐related University Rankings: Is There a Need for More Consistency or Is There Value in Breadth?

Some Shrinkage estimators based on median ranked set sampling

In this study, some shrinkage estimators using a median ranked set sample in the presence of multicollinearity were studied. Initially, we constructed the multiple regression model using median ranked set sampling. We also adapted the Ridge and Liu-type estimators to these multiple regression model. To investigate the efficiency of these estimators, a simulation study was performed for a different number of explanatory variables, sample sizes, correlation coefficients, and error variances in perfect and imperfect ranking cases. In addition, these estimators were compared with other estimators that are based on ranked set sample using simulation study. It is shown that when the collinearity is moderate, Ridge estimator using median ranked set sample performs better than other estimators and when the collinearity increases, Liu-type estimator using median ranked set sample gets better than all other estimators do. When the collinearity is smaller than 0.95, ridge estimator based on median ranked set sample is more efficient than Liu-type estimator based on same sample. However, this threshold increases as the sample size increases and the number of explanatory variables decreases. In addition, real data example is presented to illustrate how collinearity affects the estimators under median ranked set sampling and ranked set sampling.

Convex [formula omitted]-matrices and their epitopes

We investigate (0,1)-matrices that are convex, which means that the ones are consecutive in every row and column. These matrices occur in discrete tomography. The notion of ranked essential sets, known for permutation matrices, is extended to convex sets. We show a number of results for the class C(R,S) of convex matrices with given row and column sum vectors R and S. Also, it is shown that the ranked essential set uniquely determines a matrix in C(R,S).

The Efficiency Comparison and Application of Proposed Rhombus Ranked Set Sampling

A new scheme ‘Rhombus Ranked Set Sampling’ (RRSS) is developed in this research together with its properties for estimating the population means. Mathematical validation along with the simulation evaluation is presented. The proposed method is an addition to the family of different sampling methods and generalization of ‘Folded Ranked Set Sampling’ (FRSS). For the simulation process, nine probability distributions are considered for the efficiency comparison of proposed scheme from which four are symmetric and rest are asymmetric among which Weibull and beta distributions which are used twice, unlike parametric values. (Al-Naseer, 2007 and Bani-Mustafa, 2011). Through simulation processes, it is observed that RRSS is competent and more reliable relative to simple random sampling (SRS), ranked set sampling (RSS) and folded ranked set sampling (FRSS). It is noted that for all the underlying distributions, an increase in the efficiency of Rhombus Ranked Set Sampling (RRSS) is achieved via increasing the size of the sample ‘p’. Besides the efficiency comparison, consistency of the proposed method is also valued by using Co-efficient of Variation (CV). Secondary data on zinc (Zn) concentration and lead (Pb) contamination in different parts and tissues of freshwater fish was collected to illustrate the evaluation of RRSS against SRS, RSS, FRSS and ERSS (extreme ranked set sampling). The results obtained through real life illustration defend the simulation study and hence indicates that the RRSS estimator is efficient substitute for existing methods (Al-Omari, 2011).

Estimation of the Exponential Pareto Distribution’s Parameters under Ranked and Double Ranked Set Sampling Designs

In this paper, the derivation of the likelihood function for parameter estimation based on double ranked set sampling (DRSS) designs used by Sabry el.al.; (2019) for the estimation of the parameters of the power generalized Weibull distribution is considered. The developed likelihood function is then used for the estimation of the exponential Pareto distribution parameters. The maximum likelihood estimators (MLEs) are then investigated and compared to the corresponding ones based on simple random sampling (SRS) and ranked set sampling (RSS) designs. A Monte Carlo simulation is conducted and the absolute relative biases, mean square errors, and efficiencies are compared for the different designs. The relative efficiency of the DRSS estimates with respect to other designs was found to be higher in case of the exponential Pareto distribution (EP).

Inverse Engineering Preferences in the Graph Model for Conflict Resolution

In this paper, algorithms for inverse engineering preferences based on observable behavior are developed. The algorithms are based on the most commonly used stability concepts in the graph model for conflict resolution methodology and function by reducing the set of possible preference rankings for each decision-maker (DM). The reduction is based on observable moves and counter-moves made by DMs. This procedure assists stakeholders in optimizing their own decision-making process based on information gathered about their opponents and can also be used to improve the modeling of strategic interactions. A simple case study is used to illustrate the applicability of the algorithms.

Classical Methods to Estimate the Parameters of Exponentiated Weibull Distribution

In this article the Exponentiated Weibull distribution with some of its properties is considered. Classical methods, Maximum likelihood estimator method, ordinary least squares estimator method and rank set sampling estimator method are proposed to estimate all the unknown parameters (β,Ψ,θ) of the distribution. Newton–Raphson method is used to solve the above three methods, simulation procedure is used to generated some sample sizes and finally mean squares error measure are used to compare between them. We find Maximum likelihood estimator method has the smallest mean square error.

On the intersection problem for linear sets in the projective line

The aim of this paper is to investigate the intersection problem between two linear sets in the projective line over a finite field. In particular, we analyze the intersection between two clubs with possibly different maximum fields of linearity. We also consider the intersection between a certain linear set of maximum rank and any other linear set of the same rank. The strategy relies on the study of certain algebraic curves whose rational points describe the intersection of the two linear sets. Among other geometric and algebraic tools, function field theory and the Hasse–Weil bound play a crucial role. As an application, we give asymptotic results on semifields of BEL-rank two.

Generalized Hotelling T2 control chart based on bivariate ranked set techniques with runs rules

In this study, we have introduced a generalized Hotelling T2 control chart based on bivariate ranked set techniques with runs rules to identify small and moderate variations in a process mean vector. To achieve this aim, plotting statistic and control limits are formulated in generalized approaches. For evaluation purposes, power and power curves are used as performance indicators. Afterwards, power curves are drawn through Monte Carlo simulation procedures by taking into account different choices of factors. A detailed discussion about the role of factors on the performance of the proposed generalized control chart is included. Furthermore, the proposed generalized control chart with double bivariate ranked set techniques is noted to be superb compared to the other cases of single bivariate ranked set techniques. Among single and double versions of bivariate ranked set techniques, the proposed generalized control chart on the basis of median bivariate ranked set techniques is recorded as more efficient relative to the other choices under consideration. Also, comparative analysis shows that the proposed generalized control chart with supplementary runs rules performs outstandingly for detection of small and moderate variations relative to existing control charts. Special cases of the proposed generalized control chart are elaborated to highlight its features for accommodating the existing control charts. To amplify the uses and advantages of the proposed generalized control chart, a real-world example from agriculture is presented.

WITHDRAWN: Cumulative residual extropy of minimum ranked set sampling with unequal samples

WITHDRAWN: Cumulative residual extropy of minimum ranked set sampling with unequal samples

Comparison among multi-criteria decision analysis techniques: a novel method

This paper proposes a novel method of comparison among the various multi-criteria decision analysis (MCDA) techniques. The motivation behind proposing novel method of comparison comes from the fact that in spite of the presence of significant number of MCDA techniques, decision makers face difficulty in selecting appropriate MCDA technique for a particular problem under study. The reason behind this is that the applications of different MCDA techniques may result in different sets of rankings for the same problem. Such dilemma makes it difficult for the decision makers to identify the most appropriate ranking and thus the most appropriate MCDA technique for their problem. In order to solve this problem, this paper proposes to emphasize on the performance of the obtained rankings so as to identify the most appropriate ranking. Thus, the proposed performance-based comparison method is based on the performance of the obtained rankings. A total of fourteen different MCDA techniques have been compared for the purpose. These methods have been applied to a case study so as to get the rankings of the alternatives. The proposed method is applied on these obtained rankings so as to identify the most effective ranking among them, for the problem at hand. The comparison with the help of the case study establishes the effectiveness of the proposed method of comparison among MCDA techniques.

Parameter estimation of inverse exponential Rayleigh distribution based on classical methods

This paper introduces and developed a new lifetime distribution known as inverse exponential Rayleigh distribution (IERD). The new two-scale parameters generalized distribution was studies with its distribution and density functions, besides that the basic properties such as survival, hazard, cumulative hazard, quantile function, skewness, and Kurtosis functions were established and derived. To estimate the model parameters, maximum likelihood, and rank set sampling estimation methods were applied with real-life data.

ON EXTROPY PROPERTIES AND DISCRIMINATION INFORMATION OF DIFFERENT STRATIFIED SAMPLING SCHEMES

Ranked set sampling (RSS) and some of its variants are sampling designs that are applied widely in different areas. When the underlying population contains different subpopulations, we can use stratified ranked set sampling (SRSS) which combines the advantages of stratification with RSS. In the present paper, we consider the information content of SRSS in terms of extropy measure. Some results using stochastic orders properties are obtained. The effect of imperfect ranking on discrimination information is analytically investigated. It is proved that discrimination information between the perfect SRSS and simple random sampling (SRS) data sets performs better than that of between the imperfect SRSS and SRS data sets.

Designing robust modified R control charts for asymmetric distributions under ranked set and median ranked set sampling

Presence of outliers or contamination in the process control affect the construction of quality control limits badly. Therefore, more attention is to paid robust methods describing the data majority. The main focus of this study is to construct robust R charts by using ranked set sampling (RSS) and median ranked set sampling (MRSS) designs under contaminated skewed distributions such as Marshall–Olkin bivarite Weibull and Bivarite Lognormal distributions. Three robust methods named as robust modified Shewhart, robust modified weighted variance and robust modified skewness correction methods are introduced. An extensive simulation study is presented in order to analyse the efficiency of different sampling designs and robust modified R charts on the charts’ performance. These methods are evaluated in terms of their Type I risks (p). The simulation study showed that, in the contamination case, Shewhart, weighted variance and skewness correction charts based on classic estimators are affected from outliers under simple random sampling and RSS designs and cause the increase of the p values in the process. However using MRSS design is not affected by outliers. In the case of contamination, proposed robust MSC method under MRSS has the best performance for all cases. Moreover a real data application is conducted to show the superiority of proposed methods.

Проблемы вариативности музыкального жанра ренг в мугамном исполнительном искусстве молодежи

Consideration of the variability of the musical genre of rang in mugam performing arts showed that ranks arose and developed in the art of mugam as a form of vocal-instrumental music. Their melodic structure is directly related to the sections of mugam. There are numerous varieties of this relationship. Based on the analysis of the musical notation of the ranks, it was determined that in practice of performing mugam the ranks are directly related to the vocal-instrumental mugam, and this is especially important for their compositional structure. In this regard, in almost every version of mugham destgahs there is a set of different ranks, including tesnifs. The analysis of various musical records of the ranks in the musical performing arts helps to identify the features of the manifestation of this form of folk music in mugam, as well as the further development of this musical genre and musical culture as a whole. We consider it appropriate to study, primarily, the vocal-instrumental interpretation of mugham when studying mugam destgyahs and the melodic interconnections of rangs and tesnifs with sections (shobe) of mugam. After analyzing various musical notations of mugam dastgahs, we were able to trace how rengi relate to mugam shobe. It can be noted that many rengi are used in the recordings of these works associated with various performances in relation to various shobe of mugams. This feature is inherent in various mugham dastgahs – "Shur", "Segah", "Chahargah", "Bayati-Shiraz", "Shushter", "Humayun", etc. All this can be traced in musical notations, as well as in live mugham singing and sound recordings, which helps to determine the numerous variants of rengs related to these mugams. Within the framework of each mugham, dozens of rengs were created and included in musical practice. Part of this rich musical heritage is captured and preserved in sound recordings and sheet music. We believe that it is advisable to study rengi, grouping them into mugham families in order to analyze their musical language and reveal their inherent variability.

New Improved Ranked Set Sampling Designs with an Application to Real Data

This article proposes two new Ranked Set Sampling (RSS) designs for estimating the population parameters: Simple Z Ranked Set Sampling (SZRSS) and Generalized Z Ranked Set Sampling (GZRSS). These designs provide unbiased esti... | Find, read and cite all the research you need on Tech Science Press

Estimation of Population Mean by Using a Generalized Family of Estimators Under Classical Ranked Set Sampling

Estimation of population mean of study variable Y suffers loss of precision in the presence of high variation in the data set. The use of auxiliary information incorporated in construction of an es...

Maximum likelihood estimation in location-scale families using varied L ranked set sampling

Recently, a generalized ranked set sampling (RSS) scheme has been introduced which encompasses several existing RSS schemes, namely varied L RSS (VLRSS), and it provides more precise estimators of the population mean than the estimators with the traditional simple random sampling (SRS) and RSS schemes. In this paper, we extend the work and consider the maximum likelihood estimators (MLEs) of the location and scale parameters when sampling from a location-scale family of distributions. In order to give more insight into the performance of VLRSS with respect to SRS and RSS schemes, the asymptotic relative precisions of the MLEs using VLRSS relative to that using SRS and RSS are compared for some usual location-scale distributions. It turns out that the MLEs with VLRSS are more precise than those with the existing sampling schemes.

Use of Kemeny median in the algorithm of forming recommendation

The relevant nowadays question of development of the algorithmic support of recommender systems is considered. The article is devoted to the solution of the problem of forming recommendations to new users, which is based on the ideas of transition from the matrix "user-object" to the ranking of objects and the formation of recommendations to the user of the active cluster based on the construction of the resulting ranking, which is a Kemeny median on a set of rankings. The choice of Kemeny median as the resulting ranking and the choice of algorithm for its construction are justified. To reduce the complexity of calculations, it is suggested to perform aggregation of information and to use it in forming of ranking recommendations, which are based on a set of "generalized experts" for this cluster. The efficiency of the developed algorithmic support was studied and the results and recommendations were given.

Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study

The paper undertakes the problem of proper structuring of multi-criteria decision support models. To achieve that, a methodological framework is proposed. The authors’ framework is the basis for the relevance analysis of individual criteria in any considered decision model. The formal foundations of the authors’ approach provide a reference set of Multi-Criteria Decision Analysis (MCDA) methods (TOPSIS, VIKOR, COMET) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). In the empirical research, a practical MCDA-based wind farm location problem was studied. Reference rankings of the decision variants were obtained, followed by a set of rankings in which particular criteria were excluded. This was the basis for testing the similarity of the obtained solutions sets, as well as for recommendations in terms of both indicating the high significance and the possible elimination of individual criteria in the original model. When carrying out the analyzes, both the positions in the final rankings, as well as the corresponding values of utility functions of the decision variants were studied. As a result of the detailed analysis of the obtained results, recommendations were presented in the field of reference criteria set for the considered decision problem, thus demonstrating the practical usefulness of the authors’ proposed approach. It should be pointed out that the presented study of criteria relevance is an important factor for objectification of the multi-criteria decision support processes.