A fuzzy regression approach to a hierarchical evaluation model for oil palm fruit grading

Measurement of quality is an important task in the evaluation of agricultural products and plays a pivotal role in agricultural production. The inspection process normally involves a visual examination according to the ripeness standards of crops, and this grading is subject to expert knowledge and interpretation. Therefore, the quality inspection process of fruits needs to be conducted properly to ensure that high-quality fruit bunches are selected for production. However, human subjective judgments during the evaluation make the fruit grading inexact. The objectives of this paper are to build a fuzzy hierarchical evaluation model that characterises the criteria of oil palm fruits to decide the fuzzy weights of these criteria based on a fuzzy regression model, and to help inspectors conduct a proper total evaluation. A numerical example is included to illustrate the computational process of the proposed model.     

Log-det approximation based on uniformly distributed seeds and its application to Gaussian process regression

Maximum likelihood estimation (MLE) of hyperparameters in Gaussian process regression as well as other computational models usually and frequently requires the evaluation of the logarithm of the determinant of a positive-definite matrix (denoted by C hereafter). In general, the exact computation of is of O(N³) operations where N is the matrix dimension. The approximation of could be developed with O(N²) operations based on power-series expansion and randomized trace estimator. In this paper, the accuracy and effectiveness of using uniformly distributed seeds for approximation are investigated. The research shows that uniform-seed based approximation is an equally good alternative to Gaussian-seed based approximation, having slightly better approximation accuracy and smaller variance. Gaussian process regression examples also substantiate the effectiveness of such a uniform-seed based log-det approximation scheme.     

Fuzzy linear regression and its applications to forecasting in uncertain environment

Linear regression has been used for many years in developing mathematical models for application in marketing, management, and sales forecasting. In this paper, two different sales forecasting techniques are discussed. The first technique involves non-fuzzy abstract methods of linear regression and econometrics. A study of the international market sales of cameras, done in 1968 by John Scott Armstrong, utilized these non-fuzzy forecasting techniques. The second sales forecasting technique uses fuzzy linear regression introduced by H. Tanaka, S. Uejima, and K. Asai, in 1980. In this paper, a study of the computer and peripheral equipment sales in the United States is discussed using fuzzy linear regression. Moreover, fuzzy linear regression is applied to forecasting in an uncertain environment. Finally, some possible improvements and suggestions for further study are mentioned.     

Stochastic regression and its application to hedging in finance

In this paper we investigate how to employ stochastic regression to hedge risks in finance, where the risk of a security is measured by its quadratic variation process. Mykland and Zhang used this technique to demonstrate how to reduce the risk of a given security by introducing another security. In this paper, we investigate how to further reduce the remaining unhedgable risk by adding more hedging securities. Some practical guidelines on how to choose those hedging securities in practice is also given. Jing’s research was partially supported by Hong Kong RGC (Grant Nos. HKUST6011/07P, HKUST6015/08P), and Zhang’s research was supported in part by National Natural Science Foundation of China (Grant No. 10771214)     

NSD序列加权和的中心极限定理及其在EV回归模型中的应用

基于负超可加相依(简称为NSD)随机序列的性质及其一些不等式,利用随机变量的截断方法建立了NSD随机序列加权和的中心极限定理,从而推广了负相协NA随机序列的相应结论.并将其应用到变系数EV回归模型,得到了未知参数LS估计的渐近正态性.     

Fuzzy geometric programming and its application

Fuzzy geometric programming (GP) is an important optimization type. In this paper, first the origin of fuzzy GP is introduced, some recent research findings of its theory have been summarized. Then a lot of progress achieved in application is introduced in fuzzy GP, including applications in power system, environmental engineering, economic management, etc. The range of its application expects to be further expanded. Besides, as a branch of fuzzy GP, the fuzzy relation GP, rough (extension) and grey one have also been mentioned. Finally, the new research direction of fuzzy GP will be put forward.     

Complete moment convergence for weighted sums of widely orthant-dependent random variables and its application in nonparametric regression models

We establish some results on the complete moment convergence for weighted sums of widely orthant-dependent (WOD) random variables, which improve and extend the corresponding results of Y. F. Wu, M. G. Zhai, and J. Y. Peng [J. Math. Inequal., 2019, 13(1): 251–260]. As an application of the main results, we investigate the complete consistency for the estimator in a nonparametric regression model based on WOD errors and provide some simulations to verify our theoretical results.     

Z probabilistic linguistic term sets and its application in multi-attribute group decision making

Fuzzy Optimization and Decision Making - Probabilistic linguistic term set solves the problem of probabilistic distribution of linguistic terms. Due to the objective and subjective factors such as...     

Tabaistic regression and its application to the space shuttle Challenger O-ring data

In this paper, we introduce a new family of probability distributions called the tabaistic family of distributions. The members of this family can have either unimodal or bimodal probability density functions. This family can be used when the data comes from a skewed or bimodal distribution. A major application of the unimodal member of this family is in the analysis of binary or polytomous response data when covariates are present. The logistic regression (Hosmer, D.W., Lemeshow, S.: Applied Logistic Regression. Wiley, New York (2000)) and probit analysis (Finney, D.J.: Probit Analysis. Cambridge University Press, Cambridge (1971)) are widely used when the distribution is symmetric. When the distribution is asymmetric, the tabaistic regression will be a better choice. We apply the tabaistic regression to analyze the space shuttle Challenger O-ring data and will compare the results with the logistic regression and the probit analysis models.     

Variational dimension of random sequences and its application

A concept of variational dimension is introduced for a random sequence with stationary increments. In the Gaussian case, the variational dimension in the limit coincides with the Hausdorff dimension of a proper random process. Applications of the concept are illustrated by examples of neurological data and network traffic analysis.     

集对Fuzzy格及其在格表示论中的应用

用幂集格构造了集对 Ｆｕｚｚｙ 格（这与用整数对构造有理数集有相似之处）,并用它证明了完整的软代数表示定理,即定义了到自身的映射且有最大元和最小元的格为软代数的充要条件是它与某个集对 Ｆｕｚｚｙ 格的子格同构．这样,与分配格在幂集 Ｂｏｏｌｅ 格中表示相对应,软代数在集对 Ｆｕｚｚｙ 格中有表示,在理论上是很完美的     

Depth estimators and tests based on the likelihood principle with application to regression

We investigate depth notions for general models which are derived via the likelihood principle. We show that the so-called likelihood depth for regression in generalized linear models coincides with the regression depth of Rousseeuw and Hubert (J. Amer. Statist. Assoc. 94 (1999) 388) if the dependent observations are appropriately transformed. For deriving tests, the likelihood depth is extended to simplicial likelihood depth. The simplicial likelihood depth is always a U-statistic which is in some cases not degenerated. Since the U-statistic is degenerated in the most cases, we demonstrate that nevertheless the asymptotic distribution of the simplicial likelihood depth and thus asymptotic α-level tests for general types of hypotheses can be derived. The tests are distribution-free. We work out the method for linear and quadratic regression.     

Properties of fourth-order strong mixing rates and its application to random set theory

We shall define the concept of fourth-order strong mixing rates and study their properties. Results are useful for establishing a condition of the form (*) Σ_a,b,c |cum(X_o, X_a, X_b, X_c)| < ∞ or ∫|cum(X_o, X_a, X_b, X_c)| da db dc < ∞ for dependent random variables {X_a}. As an application we shall consider an evaluation of a fourth-order strong mixing rate for a random closed set Z (in the sense of Matheron) and derive the condition (*) for {X_a}, X_a being an outcome of a local measurement upon Z. The result is also applicable to point processes which admit clustering representations.     

A new method for ranking intuitionistic fuzzy values and its application in multi-attribute decision making

In this paper, we propose a new method for ranking intuitionistic fuzzy values (IFVs) by using the similarity measure and the accuracy degree of IFVs. Then we apply the proposed ranking method to multi-attribute decision making.     

Birnbaum‐Saunders quantile regression and its diagnostics with application to economic data

The Birnbaum‐Saunders (BS) distribution is a model that frequently appears in the statistical literature and has proved to be very versatile and efficient across a wide range of applications. However, despite the growing interest in the study of the BS distribution, quantile regression modeling has not been considered for this distribution. To fill this gap, we introduce a class of quantile regression models based on the BS distribution, which allows us to describe positive and asymmetric data when a quantile must be predicted using covariates. We use an approach based on a quantile parameterization to generate the model, permitting us to consider a similar framework to generalized linear models, providing wide flexibility. The methodology proposed includes a thorough study of theoretical properties and practical issues, such as maximum likelihood parameter estimation and diagnostic analytics based on local influence and residuals. The performance of the residuals is evaluated by simulations, whereas an illustrative example of income data is conducted using the methodology to show its potential for applications. The numerical results report an adequate performance of the approach to quantile regression, indicating that the BS distribution is a good modeling choice when dealing with data that have both positive support and asymmetry. The economic implications of our investigation are discussed in the final section. Hence, it can be a valuable addition to the tool kit of applied statisticians and econometricians.     

The distribution of extended discrete random sums and its application to waiting time distributions

Methodology and Computing in Applied Probability - Using the language of runs and patterns, a peak in a sequence of integers can be interpreted as observing a fall (or descent) immediately after a...     

Length of clustering algorithms based on random walks with an application to neuroscience

In this paper we show how the notions of conductance and cutoff can be used to determine the length of the random walks in some clustering algorithms. We consider graphs which are globally sparse but locally dense. They present a community structure: there exists a partition of the set of vertices into subsets which display strong internal connections but few links between each other. Using a distance between nodes built on random walks we consider a hierarchical clustering algorithm which provides a most appropriate partition. The length of these random walks has to be chosen in advance and has to be appropriate. Finally, we introduce an extension of this clustering algorithm to dynamical sequences of graphs on the same set of vertices.     

The maximum size of the planar sections of random spheres and its application to metallurgy

A theorem of this paper proves that if the size distribution of random spheres is generalized gamma, its Wicksell transform and other related distributions belong to the domain of attraction of the Gumbel distribution. The theorem also shows the attraction coefficients of the distributions. The fatigue strength of high-strength steel is closely related to the maximum size of nonmetallic inclusions in the region of maximum stress of the steel. Murakami and others developed a method, making use of the Gumbel QQ-plot, for predicting the maximum size from the size distribution of inclusion circles in microscopic view-fields. Based on the Gumbel approximation of the maximum of wicksell transforms, a modified and extended version of Murakami's method is justified, and its performance is evaluated by simulation.