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This article is devoted to the regeneration of air filters of Mercedes-Benz buses, the number of optimal regenerations of clogged air filters is justified. The dynamics of changes in the aerodynamic resistance of air filters is experimentally and theoretically justified, as well as second-order polynomials are obtained by applying mathematical statistics methods to predict changes in their resistance. [ABSTRACT FROM AUTHOR]

This article presents the results of solving various classification problems by the algorithms proposed in this study. Computational experiments were carried out in such a way that their results were comparable with already known solutions. This made it possible to assess the strengths and weaknesses of the minimax approach to data analysis and determine the ways for further research. Of the traditional methods of cluster analysis, linguistic data analysis was chosen, since the method of nuclear clustering has "grown" and is developing in this approach. The two main problems of data processing - accuracy and speed - with large dimensions of processed arrays can be solved by developing accurate and fast algorithms and using new info communication technologies on which these algorithms are implemented. The present work is devoted to solving these two problems. A nuclear clustering method is proposed within the framework of structural or data mining (Data Mining) and the possibilities of its operation in a distributed environment are evaluated. Indeed, the emergence of modern technologies for structural data analysis Data Mining is associated with a new round in the development of data processing tools and methods. The goal of this approach is to uncover hidden rules an patterns in datasets, since the human brain cannot identify more than two or three relationships, even in small samples. Mathematical statistics often turns out to be effective only for testing hypotheses already obtained by Data Mining, and the formulation of hypotheses is performed automatically in the course of a computational experiment. Today this technology is widely used in business (banking, insurance, trade), telecommunications. Foreign experience shows that the use of Data Mining can give an economic effect (10-70 times) as high as in comparison with the initial costs. [ABSTRACT FROM AUTHOR]

The variational series is the starting point for many applied problems, and this concept is widely used in mathematical statistics and other fields of knowledge. Therefore, a large number of publications are devoted to the study of distributions of members of the variational series. In classical mathematical statistics, the sample size for which a variation series is formed is considered to be deterministic. [ABSTRACT FROM AUTHOR]

Statistical literacy ability is one of the abilities that students need to have. One of the efforts to build numeracy literacy skills is by mastering mathematics in statistical material. This research article describes statistical literacy skills in terms of mathematical communication skills. The type of this research was qualitative research. The subject of this study is a student of SMA Negeri 1 Gemolong for the 2022/2023 academic year. The selected students consisted of 3 students, with details of one student in each category. This research instrument includes statistical literacy test questions, mathematical communication skills tests, and interviews. Data validity used time triangulation with the interview method. Data analyses were done through data collection, reduction, presentation, and conclusion. Based on the findings, subjects with high communication skills will efficiently work on problems understanding data, interpreting data, and communicating statistical literacy data. The subjects with medium mathematical communication skills are already understanding and analyzing data correctly, but there are still those who are not correct in sharing data meanwhile, subjects with low mathematical communication skills are still unable to understand, interpret, and communicate, so there are still many mistakes in answering statistical literacy questions. [ABSTRACT FROM AUTHOR]

Defragmenting is the process of correcting the structure of wrong thinking to get the right understanding. This misunderstanding can occur because students have not been able to implement their metacognition in problem-solving. This study aims to describe students' metacognitive structural errors in solving statistical problems and their defragmenting efforts. The research method used was a qualitative descriptive approach with a total of 28 students as research subjects. The data collection technique used was by using statistical tests, observations, interviews, and video recordings. The process of analyzing research data was carried out by data reduction techniques, data presentation, and conclusion. The results showed that students experienced metacognitive errors in solving the statistical problems given. These metacognitive errors were made by students in exploring the meaning of mathematical problems or in the aspect of understanding the problem and determining the right solution strategy or in the planning aspect. After students received the intervention and defragmenting efforts, it was found that students' metacognition in the aspect of understanding the problem and planning aspects became optimal so that students obtained the right mathematical problem-solving solution. [ABSTRACT FROM AUTHOR]

The article presents the results of an experimental study conducted to assess the influence of the diameter of the sensitive element of the sensor on the mass measurement error. The work used elements of probability theory and mathematical statistics, as well as the basic postulates of metrology. As a result of evaluating the influence of the diameter of the sensitive element of the load cell Ø27+0.05 on the mass measurement error, it had found that a change in the diameter of the hole on which the load cell has located affects the main measurement error mainly at the upper loading points. Increasing the diameter slightly increases the sensitivity of the device, while decreasing it reduces it. The variation stays the same when measuring the load cell diameter. The conducted studies show that the studied sensors have suitable as corresponding to the 3rd accuracy class. [ABSTRACT FROM AUTHOR]

Methods of improving the quality control of products specified by a large amount of parameters are proposed. The methods are based on multidimensional mathematical statistics. Numerical examples are given to illustrate the methods. [ABSTRACT FROM AUTHOR]

Unemployment and its effects on the country's economy have been important throughout the history of market economies. There are two approaches to unemployment: firstly, it is a large problem due to the withdrawal of labor resources from the economic cycle; secondly, it is an opportunity to redistribute labor resources to new economic sectors. We believe that there can be another approach: the unemployment level can be indicative of the state of the economy, especially during crises. Therefore, this research is highly relevant during the COVID crisis. The purpose of this research is to calculate the effects of the COVID crisis on the unemployment level in post-Soviet countries. To accomplish the purpose set, we used the historical method, comparisons, and mathematical statistics. The results of the research showed that despite the similarities between the causes of the crises, the existing economic models in the post-Soviet countries respond differently to shocks. This can be manifested in unemployment level variations in the republics in question depending on the remoteness of the market transformation. The effects of the economic situation on the unemployment level (Okun's law) in the post-Soviet counties differed under various crises, which is confirmed by the differences in point distributions in 2008-2009 and 2020. [ABSTRACT FROM AUTHOR]

The demands of learning mathematics in the 21st century are to provide learning that can emphasize reasoning, forming an attitude, and cultivating problem-solving skills in the application of mathematics. Mathematical literacy is the competence of mathematics to interpret and apply mathematical concepts in various situations. This study aims to describe the competence of mathematical literacy of junior high school 5 Kudus students' in solving HOTS problems in statistical materials. The subjects of this study were 33 students who were reduced to one student each with medium and low high ability. Mathematical literacy tests and interviews were used in data collection in this study. The results showed that in problems with the level of analyzing, subjects with high competence were not able to represent. Whereas subjects with moderate and low competence cannot perform representation and reasoning. On the problem of the level of evaluating subjects with moderate competence meet all indicators, while subjects with high ability are simply not able to do reasoning. Subjects with low ability are only capable of performing communication and mathematical operations. Factors affecting students' errors in representation and reasoning are errors in the determination of answers. While the factor influencing errors in mathematization and strategy planning is the mathematization itself. [ABSTRACT FROM AUTHOR]

This study purpose to develop a Student Worksheet based on mathematical literacy. This study uses the ADDIE model development with the stages of analysis, design, development, implementation and evaluation. To determine the validity of the student worksheet assessed from the validation of material experts, media experts, teachers and student response questionnaires. The subjects of this study were 6 students of class VIII as a limited trial and 32 students of class VIII E as the subject of field trials. The student worksheet developed contains KI, KD, learning objectives, steps to find concepts related to everyday life, questions derived from PISA and based on mathematical literacy. The results of material validation obtained an average score of 3.22 which was categorized as "good", the results of media expert validation obtained an average score of 3.84 including the "very good" category, the results of teacher validation obtained an average score of 3.36 which was categorized as " good", from the results of the student response questionnaire obtained an average score of 3.05 in the practical category so that the student worksheet is said to be practical, from the student learning outcomes it shows 75% complete in solving problems with a score above the average so that the LKPD is said to be "effective" and the results of the response from 3 teachers got an average of 3.4 in the "very decent" category. From the validation results, student response questionnaires, student learning outcomes and teacher responses, it can be said that the student worksheet based on mathematical literacy on statistical material is valid, effective, and feasible to be used as teaching material in the implementation of mathematics learning. [ABSTRACT FROM AUTHOR]

The paper presents the results of research on the impact of selected types of speed bumps, located in the streets of the city road network, on the instantaneous speed of passenger cars in free flow traffic conditions. The research considered different speed bumps. All types of speed bumps occurred to be very effective in a traffic calming. The applied parametric tests of a statistical significance showed that, for the sake of mathematical statistics, the differences in the instantaneous speed of vehicles at the speed bumps are significant in relation to the instantaneous speed of vehicles on the inter-junction sections. The instantaneous speeds of passenger cars at speed bumps were over 60% lower in relation to the speeds achieved by drivers of those cars in the inter-junction sections. [ABSTRACT FROM AUTHOR]

Building materials and structures are exposed to a bacterial environment with high humidity of the outside air, humid and wet conditions in buildings, and the presence of liquids used in the production process. A humid environment is favorable for the colonization of bacteria on the surface and penetration into the thickness of materials, which release metabolic products in the process of life – sulfuric acid, nitric acid, ammonia. When they interact with a solid substance of the material, substitution reactions, biocorrosion, and structural disturbances, a decrease in the material's performance, accompanied by a change in the mass of the samples, occur. The compositions of industrial dry building mixtures have been determined, the products of which have the greatest and least resistance to the influence of an aggressive environment. A statistical approach to solving the problem of establishing the most unfavorable ratio of components in a model aqueous solution of various compositions, simulating the products of bacterial metabolism, is proposed: sulfuric acid – 2%, nitric acid – 1%, and ammonia – 2%. The least effect on cement composites is provided by an environment without ammonia, with a content of 2% sulfuric acid and 1% nitric acid. [ABSTRACT FROM AUTHOR]

The conditions of navigation on the Northern Sea Route (hereinafter referred to as the NSR) are largely determined by changes in the average thickness and concentration of the ice cover in its sections. These changes can be caused by different natural processes, a more complete understanding and consideration of which can significantly improve the quality of medium-term forecasts of ice conditions in the Arctic seas. The areas of the NSR with the most intensive shipping are currently located in the Kara Sea, where, despite difficult ice conditions particularly in the winter-spring period, navigation is year-round. The authors put forward a hypothesis that interannual variations in ice thickness and concentration of some sections of the Kara Sea in winter-spring months can be significantly influenced by changes in the Norwegian Sea level. The paper verifies this assumption and provides an assessment of current trends in the Norwegian Sea level variations. The research methodology is based on standard methods of mathematical statistics. GLORYS12v.1 reanalysis is used as a data source. It is shown that a large number of areas for which the hypothesis is true exist in the Kara Sea in certain months. For the same months, an increasing trend in interannual variations in the mean level of the Norwegian Sea is found for the last two decades. Qualitative forecasts of the Kara Sea ice thickness and concentration are provided which will be relevant as long as the Norwegian Sea level dynamics does not change and the identified relationships stay significant. [ABSTRACT FROM AUTHOR]

Successful investment in a construction project involves an analysis of potential risks and the ability to manage them. The risks associated with the economic activity of the investment project are well studied and considered directly. But many issues related to ecology, production and transport are not considered and unforeseen absolute risks appear, the implementation of which threatens to increase the cost of the project. Traditional approaches to managing risk events are: insurance, diversification and redundancy, they only lead to an increase in the cost of a construction project. This negatively affects the investor's decision to invest resources in the project. The low level of investment in construction, where energy-efficient technologies are used, shows that the analysis of potential investment risks only from an economic point of view in modern realities is insufficient and requires the inclusion in its consideration of "absolute" risks, the management of which will interest the investor to invest resources in the project. In order to solve the situation that has arisen, it is reasonable to use an information system, based on the principle of analyzing potential "absolute" risks and instructions for managing them, which makes it possible to identify the weaknesses and strengths of an investment construction project, increases organizational and technological reliability and gives the investor an understanding of the required resources for the implementation of the project. Reliability is based on probability theory and mathematical statistics. As with any static studies and probabilistic calculations, assumptions are made about the nature of the distribution of various kinds of failures affecting the reliability of the system. This technique makes it possible to increase the organizational and technological reliability of construction projects using energy-efficient technologies, and thereby optimize construction time, logistics costs and construction costs. By analyzing and managing "absolute" risks, the model makes it possible to effectively organize construction production, reduce time and financial costs for the process of identifying and analyzing potential risk events. [ABSTRACT FROM AUTHOR]

Students' learning independence is still lacking, which is the reasons for conducting this research. The purpose of this study is to determine the effectiveness of the development of learning design through statistical concepts using the Realistic Mathematical Education (RME) approach to mathematical communication skills implemented in Hypothetical Learning Trajectory (HLT), teacher books and student books are valid and practical. The method used in this study is the combination of the Plomp design research model and the Gravemeijer & Cobb model. The research subjects were students of class VIII MTs. The data collection technique used posttest test from small group students. The results of the posttest test of students reached a value above the KKM (75) with an average of 87.96 and the average student learning independence during the learning process reached 76.07 with a good category. Therefore, the development of learning design based on RME approach is effective for students' mathematical communication skills in statistical material and can increase students' learning independence. [ABSTRACT FROM AUTHOR]

Today, the tasks of managing the stages of the life cycle of capital construction projects in Russia are becoming relevant due to a number of changes in the regulatory, technical and regulatory documents. The article deals with the problem of consolidating the activities of all participants in the stages of the life cycle of an object - research, design, construction, operation. The purpose of the work is to identify the key parameters that affect each stage of the building cycle efficiency and control them. The article presents the results of the analysis of Russian and international scientists on the research topic. The research methodology is built using the methods of system analysis, construction systems engineering, methods of mathematical statistics. The parameters influencing the state of the system with regard to the stages of the project life cycle, including justification of investments, engineering surveys, architectural and construction as well as organizational and technological design, and construction are identified. The results of the analysis of the stages of operation, reconstruction, modernization, overhaul, restoration, decommissioning, demolition and disposal of the project will be presented in detail in further research. [ABSTRACT FROM AUTHOR]

The aim of our work was to study the mechanical characteristics in conditions of flat stress state and widen the current knowledge of construction plywood appliance. It was decided that the best method for this investigation was to examine randomly selected plywood batches and analyse the results with the use of mathematical methods of statistics. The specimens were made up of plywood that was typified by different veneer grades. The main two groups of the specimens were manufactured with PF and UF resin. The conducted tests under the main types of flat stress in material (linear tension, compression and transverse bending) showed the strengths and their correlation between theoretical and obtained values. Based on the carried on plywood research the linear correlation dependence of veneer thickness on strength limit was obtained along and across fibres of external layers under compressive stress. Our experiments prove that veneer grade does not affect the tensile strength independent of the applied load direction regarding the fibre of external layers. This means that veneer grade defines only the quality of appearance. The mentioned above accessed results could be used for practical calculations during the design and manufacturing. [ABSTRACT FROM AUTHOR]

In the article, the study of chaotic dynamics of complex non-stationary biomedical systems, and in particular, a special type of chaos arising in the parameters that describe these systems is discussed. A special type of chaos is understood as the existence of irreproducible aperiodic regimes in the dynamic systems: x(t0) = var and f(xi) = var, when t → ∞. In contrast to the Lorenz deterministic chaos, in such systems not only the process is irreproducible, but the initial state of the system is also always irreproducible x(t0). The study is based on the use of methods of nonparametric mathematical statistics, methods of nonlinear dynamics (calculation of the senior Lyapunov exponent), as well as calculation of the parameters of quasi-attractors, which qualitatively and quantitatively describe the chaotic dynamics of biomedical signals. Using the analysis of autocorrelation, it was shown that the parameters of biomedical systems, using the example of cardio signal elements (time series of cardio intervals) of the cardiovascular system, have a strictly chaotic structure and a non- linear trend line. The calculation of the senior Lyapunov exponent showed that there is a constant change of sign (+, -, 0) at different time intervals of the cardio signal, which also proves the presence of chaos, different from Lorentz chaos, which has a positive sign for the senior Lyapunov exponent, as well as a repeated initial state of the system x(t0). A method has been developed that made it possible to quantitatively and qualitatively describe the chaotic dynamics of the behavior of the state vector of the system, obtain objective information about changes in the functional state of the system, and also warn about these changes in time (if pathologies), what creates conditions for physiological monitoring of the status of the functional systems of the human body. [ABSTRACT FROM AUTHOR]

The work with specific examples examines the main methods and techniques for processing the results of an experiment, the knowledge of which is necessary for a modern economist in analyzing the mass data on agriculture. The use of mathematical statistics methods for calculating specific indicators is shown. [ABSTRACT FROM AUTHOR]

The article analyzes the results of the experiment of the controlled bus of the NefAZ-4208-03 bus used to transport workers of the Almalyk mining and metallurgical plant to various objects, using the method of mathematical statistics. A scientifically substantiated tire mileage standard has been developed, taking into account the real operating conditions of JSC "AМMС" and the reliability and safety of vehicles has been increased. On the basis of the research, it was recommended for the NefAZ-4208-03 rotational bus to set the mileage standard for radial tires of standard size 425 / 85R21, equal to 50,000 km. [ABSTRACT FROM AUTHOR]

The 6th ISM International Statistical Conference (ISM-VI) took place from September 19th to 20th, 2023, at the Concorde Hotel in Shah Alam, Selangor, Malaysia. The conference, organized by Universiti Teknologi MARA and the Malaysia Institute of Statistics (ISMY), aimed to promote statistical research and its applications. The conference covered various topics, including applied statistics, big data analytics, operational research, statistical modeling, statistical software and computing, and time series analysis. The proceedings of the conference consist of 63 selected papers that have been peer-reviewed and cover a range of statistical principles and practical applications. The conference highlighted the growing trend of incorporating non-parametric methods and machine learning in statistical theory and application. The organizers expressed their gratitude to the sponsors and participants for their contributions to the conference. [Extracted from the article]

In the presented work, the author analyzed the indicators and characteristics of the maintainability of large units and assembly units of heavy engineering products. The calculation of operational indicators and the distribution law of the recovery and maintenance time are given. The paper shows that the random nature of production and operational factors predetermined the widespread use in the theory of reliability of the mathematical apparatus and methods of the theory of probability, the theory of random functions and mathematical statistics. In particular, their application to describe changes in the state of devices, analytical determination and statistical assessment of reliability characteristics. The relevance of this work is the possibility of practical adaptation of maintainability indicators for decomposed units with varying degrees of detail. The results of the work are presented in the form of practical recommendations for the operation of large mechanical engineering products. [ABSTRACT FROM AUTHOR]

The article is devoted to the method of choosing the dissipative parameters of the elastic element of the side support of the freight car body. Based on application of methods of simulation of the movement of rail vehicles, mathematical statistics and methods of statistical processing of experimental data and the use of methods of frequency analysis of time dependences the authors of the study have developed an original method for choosing this parameter. The method described in the article allows to select the parameters of the dissipation of the elastic element of the side support of the freight car body within the stage of designing which allows cutting the economic expenses within the stage of freight car designing and increasing traffic safety. [ABSTRACT FROM AUTHOR]

The paper deals with investigation of the important problem of processing the ophthalmic data on the post-operation status of patients. The groups of patients differ by the type (technology) of fixing the intraocular lenses (IOL). Validity of each type of technology is estimated by computation of criteria for distinction of data between groups. The initial information comprises measurements of several ophthalmic indices. The samples on each index are very short; in each index, as a rule, the samples of patients’ groups overlap each other; any probabilistic characteristics of the measuring indices are unknown; any probabilistic characteristics of the measuring errors are also unknown. So, the standard methods of mathematical statistics can be applied only in the formal way and have shown to be inefficient. In contrast, the Hausdorff distance (from the set theory) as the criterion of distinction between two samples (both for one- and, especially, for two-dimensional indices) demonstrated to be reliable to distinct the patient’s status. Computations of the Hausdorff distance are valid for any relative location of point sets under comparison. [ABSTRACT FROM AUTHOR]

The article is devoted to solving the actual problem - to reduce acoustic pollution which is made by rail. The purpose is to ensure the acoustic rail safety through physical modeling of the acoustic pollution dynamics of the railways process environment, followed by mathematical description of this process on the basis of methods of probability theory and mathematical statistics. Research methods were based on the analytical generalization of scientific and technical results of dynamic systems research on the basic provisions of the system analysis, theory, simulation of technical systems, methods of mathematical statistics and probability theory. A sound wave in the course of its dynamic interaction with physical objects in each stage changes its physical characteristics. Therefore, the essence of the physical process dynamics of the acoustic pollution caused by rail can be expressed in mathematical relationship characterizing the probability of the process realization. The resulting study of the mathematical description of dynamics physical nature of the acoustic pollution of the process fluid rail enables a scientific foundation for these or other technical solutions aimed at reducing the acoustic discomfort in the surrounding territories of populated areas. [ABSTRACT FROM AUTHOR]

The f-divergence of Csiszar is well-known in information theory and statistical inference as a measure of the distance between two probability distributions. The f-divergence is generated by a convex function. A weaker form of the f-divergence is known as a f-disparity difference which is generated by a f-disparity function which is not necessarily convex. The universal portfolio generated by a f-disparity difference is studied empirically with respect to the accumulation of wealth of the investor. It is possible to increase the investor wealth using such a portfolio in investing in a stock market. [ABSTRACT FROM AUTHOR]

In recent years, introductory statistics has become a necessary course for Malaysian undergraduates, especially for those enrolled in non-mathematics/statistics oriented programmes. This is in line with the rapid growth of data science (and big data). However, most undergraduates’ interest to learn statistics declined and resulted in the ineffective acquisition of statistical knowledge and skills. Classroom engagement, being the key to effective learning is also responsible to inculcate in undergraduates the interest to learn statistics. Accordingly, this paper described undergraduates perceptions of statistics classroom engagement. A survey was conducted on 200 students taking an introductory statistics course in a Malaysian public university. The questionnaire comprised 37 attributes pertaining to 4 dimensions of classroom engagement. Undergraduates’ ratings on the attributes were analysed using fuzzy conjoint model. Our findings revealed that undergraduates had highly negative perceptions of their statistics classroom engagement. In particular, they did put effort into classroom learning (behavioural engagement); often got worried when learning new things about statistics (emotional engagement); agreed that they did just enough to get by (cognitive engagement), and never tried to work with their peers who can help in statistics (social engagement). As higher engagement cultivates students’ interest ro learn statistics, negative and neutral perceptions should be eradicated. Several measures to achieve this are discussed. [ABSTRACT FROM AUTHOR]

Finite element (FE) analyses of reinforced concrete (RC) structures or structural elements using nonlinear concrete material models are currently a subject of interest for many scientific institutions or departments. Obtaining of relevant results from such analyses depends on a number of aspects, including (for example) the level of complexity of the computational model used, correct boundary conditions, the correct definition of parameter values of the material models used, etc. A key aspect from the above-mentioned aspects is especially the problematic of the definition of correct parameter values of the used material models. Defining the correct parameter values of the material models is often a very difficult task because we usually do not have enough knowledges about the given parameters or their possible ranges. However, the current level of computational technology combined with the current state of knowledge in the fields of mathematical statistics, artificial neural networks and optimization allows us to successfully deal with the given task by so called inverse identification of parameters whose correct numerical values we need to obtain. The aim of this paper is to show the possibility of using the optimization-based inverse identification of parameter values of a nonlinear concrete material model for FE analysis of structural element which is a high RC beam subjected to a four-point bending. For this purpose, the results of the corresponding experiment are used. [ABSTRACT FROM AUTHOR]

Geometric process (GP) is widely used as a stochastic monotone model in many practical applications since its introduction. However, its scope is still limited. Due to this limitation, Wu, 2018 proposes a new stochastic process named as doubly geometric process (DGP). After defining a new stochastic process, estimation problem of the model parameters arises naturally. In this paper, the statistical inference problem for the DGP is considered when the distribution of the first inter-renewal time is assumed to be an exponential distribution. The model parameters of the DGP and the parameter of distribution are estimated by using the maximum likelihood (ML) method. The asymptotic distributions of the ML estimators are obtained. Finally, a Monte Carlo simulation study is carried out to evaluate the performance of the estimators. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to introduce a new method we call “Tridiagonal Folded Kernel Enhanced Multivariance Products Representation (TFKEMPR)”, which involves both Tridiagonal Kernel Enhanced Multivariance Products Representation (TKEMPR) and Tridiagonal Folmat Enhanced Multivariance Products Representation (TFEMPR) as its very specific circumstances. [ABSTRACT FROM AUTHOR]

This article describes the methods of processing data on the extraction of natural resources of a particular region on the basis of mathematical modeling and statistics. A statistical study of these natural resources is new and can make a significant contribution to the theory and practice of the efficient use of natural resources. The research plays an important role in formation of new business technologies for enterprises operating in the natural resources sector. The identification of extraction trends for natural resources can positively affect the rational use of natural resources on the regional level. [ABSTRACT FROM AUTHOR]

The task of estimation of the tails of probability distributions having small samples seems to be still opened and almost unsolvable. The paper tries to make a step in filling this gap. In 2017 we introduced six new characteristics of the heaviness of the tails of theoretical distributions. They rely on the probability to observe extreme outliers. The main their advantage is that they always exist. This work presents some new properties of these characteristics. Using them six distribution sensitive estimators of the extremal index are defined. A brief simulation study compares their quality with the quality of Hill, t-Hill, Pickands and Deckers-Einmahl-de Haan estimators. [ABSTRACT FROM AUTHOR]

Fuzzy time series has received increasing intentions since the first definition of fuzzy time series was introduced in 1993 by Song and Chissom. Then many studies proposed new fuzzy time series models. One of the steps in developing fuzzy time series model is partitioning the universe of discourse into different lengths of intervals. However, the performance of fuzzy time series model can be affected by interval length factor. Therefore, the objective of this study is to investigate the performance of Weighted Subsethood fuzzy time series model with different lengths of interval. By using the familiar data in fuzzy time series study, the historical enrollments of University of Alabama data, seven different number of interval cases were generated. The results show that partitioning the data into four intervals has the minimum forecasting error. [ABSTRACT FROM AUTHOR]

In this paper, a multiple un-replicated linear functional relationship model is derived where its maximum likelihood estimators are obtained from a single p -1 dimensional fitted plane. Its properties of unbiasedness and consistency were investigated using Taylor approximation and Fisher information matrix respectively.Simulations were conducted to investigate the effect of different sizes of error variances and sample sizes. The developed model is applied to real estate with housing data from Petaling Jaya, Selangor state. The results obtained show that the fitting and predictive abilities of the proposed model are stronger as compared to multiple regression model when applied to the training and testing samples respectively. [ABSTRACT FROM AUTHOR]

ARMA type models are widely used in forecasting time series data. Recently, a class of models known as Generalised ARMA (GARMA) has been introduced to reveal some hidden features in time series data which cannot be identified by standard time series models like ARMA. GARMA type models are recognized by the use of an additional parameter as an index,δ. The properties for GARMA(1,1;δ, 1) and GARMA(1,2;δ, 1) models have already been established. In this study, the properties of higher model, i.e. the GARMA(1,3;δ, 1) model is proposed by establishing the Maximum Likelihood method for estimating the parameters. This method adopts the Hannan-Rissanen algorithm for preliminary estimation. The usefulness of the model is illustrated by some numerical examples. The GARMA(1,3;δ, 1) model is fitted to a real data set and for comparison, the data is also fitted with GARMA(1,1;δ, 1) and GARMA(1,2;δ, 1) models. Based on the root mean squared error (RMSE) and the mean absolute percentage error (MAPE), the forecast performance for GARMA(1,3;δ, 1) model is the best as compared to the other two models. Hence, it can be concluded that the higher order model should also be considered for modeling time series data. [ABSTRACT FROM AUTHOR]

Various fuzzy time series (FTS) forecasting methods have been proposed by the previous researchers. The discrete fuzzy sets and trapezoidal fuzzy numbers (TrFNs) have been used as a basis to calculate the forecasted values. However, by representing the data with discrete fuzzy sets, the forecasted range under different degree of confidence (DDoC) cannot be obtained. While for the data represent in TrFNs, the forecasted values in term of TrFNs need to be defuzzified in order to calculate the forecasting accuracy such as mean square error (MSE) and root mean square error (RMSE). During the defuzzification process, some information has been dissipated from the data. Hence, it can contribute to the lack of ability to grasp the sense of uncertainty that has been preserved throughout the forecasting process. In this paper, we propose a new forecasting FTS method based on TrFNs and similarity measure concept. The similarity measure concept based on area and height is used to evaluate the forecasting accuracy. Besides, it can be used as an alternative approach to measure the accuracy without going through the defuzzification process. Keywords: forecasting, fuzzy, similarity [ABSTRACT FROM AUTHOR]

Using The historical stock price data to set up a sequence model to explain the intrinsic relationship of data, the future stock price can forecasted. The used models are auto-regressive model, moving-average model and autoregressive-moving-average model. The original data sequence of unit root test was used to judge whether the original data sequence was stationary. The non-stationary original sequence as a first order difference needed further processing. Then the stability of the sequence difference was re-inspected. If it is still non-stationary, the second order differential processing of the sequence is carried out. Autocorrelation diagram and partial correlation diagram were used to evaluate the parameters of the identified ARMA model, including coefficients of the model and model order. Finally, the model was used to forecast the fitting of the Shanghai composite index daily closing price with precision. Results showed that the non-stationary original data series was stationary after the second order difference. The forecast value of shanghai composite index daily closing price was closer to actual value, indicating that the ARMA model in The paper was a certain accuracy. [ABSTRACT FROM AUTHOR]

The aim of the paper is to analyze experimental data on the dynamic response of the marble specimen in uniaxial compression. To make it we use the methods of mathematical statistics. The lateral surface velocity evolution obtained by the laser Doppler vibrometer represents the data for analysis. The registered data were regarded as a time series that reflects deformation evolution of the specimen loaded up to failure. The revealed changes in statistical parameters were considered as precursors of failure. It is shown that before failure the deformation response is autocorrelated and reflects the states of dynamic chaos and self-organized criticality. [ABSTRACT FROM AUTHOR]

This research substantiates an approach to interval estimation of time series trend component. The well-known methods of spectral and trend analysis are used for multidimensional data arrays. The interval estimation of trend component is proposed for the time series whose autocorrelation matrix possesses a prevailing eigenvalue. The properties of time series autocorrelation matrix are identified. [ABSTRACT FROM AUTHOR]

We discuss some problems that arise when applying statistical inference to data with the aim of disclosing new functionalities. A predictive model analyzes the data taken from experiments on a specific material to assess the likelihood that another product, with similar structure and properties, will exhibit the same functionality. It doesn't have much predictive power if variability occurs as a consequence of a specific, non-linear behavior. We exemplify our discussion on some experiments with biased dice. [ABSTRACT FROM AUTHOR]

A comparative study of logistic regression, support vector machine (SVM) and least square support vector machine (LSSVM) models has been done to predict the slope failure (landslide) along East-West Highway (Gerik-Jeli). The effects of two monsoon seasons (southwest and northeast) that occur in Malaysia are considered in this study. Two related factors of occurrence of slope failure are included in this study: rainfall and underground water. For each method, two predictive models are constructed, namely SOUTHWEST and NORTHEAST models. Based on the results obtained from logistic regression models, two factors (rainfall and underground water level) contribute to the occurrence of slope failure. The accuracies of the three statistical models for two monsoon seasons are verified by using Relative Operating Characteristics curves. The validation results showed that all models produced prediction of high accuracy. For the results of SVM and LSSVM, the models using RBF kernel showed better prediction compared to the models using linear kernel. The comparative results showed that, for SOUTHWEST models, three statistical models have relatively similar performance. For NORTHEAST models, logistic regression has the best predictive efficiency whereas the SVM model has the second best predictive efficiency. [ABSTRACT FROM AUTHOR]

The classical portfolio optimization problem does not assume asymmetric behavior of relationship among asset returns. The existence of asymmetric response in correlation on the bad news could be important information in portfolio optimization. The paper applies Dynamic conditional correlation model (DCC) and his asymmetric version (ADCC) to propose asymmetric behavior of conditional correlation. We analyse asymmetric correlation among S&P index, bonds index and spot gold price before mortgage crisis in 2008. We evaluate forecast ability of the models during and after mortgage crisis and demonstrate the impact of asymmetric correlation on the reduction of portfolio variance. [ABSTRACT FROM AUTHOR]

We describe efficient algorithms for adaptive multiscale approximation of functions that are sampled with uneven density and/or have important small-scale detail limited to small portions of their domain. Our algorithm constructs the approximation from the top down, using a special least squares fitting of the residual at each level, followed by a basis reduction procedure to discard elements that contribute very little to the approximation. An important feature of these algorithms is their generality, since they are independent of domain dimension and shape, mesh, and approximation basis. Another important feature is that they do not need to generate the full basis at each level. [ABSTRACT FROM AUTHOR]

In this article, we have improved some unbiased ratio type estimators for estimating the finite population variance of the study variable. The proposed estimators are developed with the aid of the variance estimators given by Upadhyaya and Singh [8] and Kadilar and Cingi [1] in simple random sampling. We have derived the expressions of the variance of the proposed estimators. We have obtained the comparison conditions for which the variance values of the proposed estimators are smaller than MSE values of estimators given in Upadhyaya and Singh [8] and Kadilar and Cingi [1]. The real data set taken from the literature is used for the numerical comparisons. [ABSTRACT FROM AUTHOR]

In this paper we investigate the performance of a copula type Gumbel-Barnett, for prediction of the dependence between two variables, X and Y. We fit a copula, using a sample of observations collected at time t and we define predictive areas, at different levels, to detect specific changes in a sample at time t +1, both samples are governed by the same law (copula). The study addresses the more general problem of detecting dependence changes during different periods of time. This work is developed under a Bayesian perspective, a procedure that allows working with small sample sizes and under different assumptions introduced in the model through the prior distribution. [ABSTRACT FROM AUTHOR]

In this paper the method of the n-dimensional identification and of the scalar identification is considered for a linear model and the necessary conditions for the suitability of this model depending on the measuring errors are formulated. The example of using this method to estimate the drift angle in the model of ship dynamic is considered. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed some ratio type estimators of population mean using known information of auxiliary variable under truncated ranked set sampling. To see the performance of suggested estimators a simulation study is done. [ABSTRACT FROM AUTHOR]

This paper presents evidence from Monte Carlo simulation aimed at exploring power of heteroskedasticity tests to verify presence of various patterns of non-constant variances in linear models. Three independent MC simulations were set up to investigate impact of error term variance changing with power of the proportionality factor (schemes 1 and 2) or in response to variance multiplication constant applied to a subset of data (scheme 3). Empirical power was shown to vary in accordance with the simulated form of the skedastic function and sample size. Tests mainly showed adequate power for the skedastic function in scheme 1 and to a lesser extent for variance function in scheme 3. On the other hand, skedastic functions simulated in scheme 2 were the most difficult to detect by most heteroskedasticity tests. [ABSTRACT FROM AUTHOR]

Some new stochastic algorithms are suggested to determine the minimal eigenvalue for the first boundary value problem for Laplace operator. [ABSTRACT FROM AUTHOR]