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Shahrastani Shahram Yaghoobzadeh Shahrastani,
Volume 23, Issue 2 (3-2019)
Abstract
In this paper, a new estimate of exponential type of auxiliary information to help simple random sampling without replacement of the finite population mean is introduced. This new estimator with a few other estimates using two real data sets are compared with the mean square error.
, ,
Volume 23, Issue 2 (3-2019)
Abstract
In this paper, in order to establish a confidence interval (general and shortest) for quantiles of normal distribution in the case of one population, we present a pivotal quantity that has non-central t distribution. In the case of two independent normal populations, we construct a confidence interval for the difference quantiles based on the generalized pivotal quantity and introduce a simple method for extracting its percentiles, by which a shorter confidence interval can be constructed. We will also examine the performance of the proposed methods by using simulations and examples.
Javad Ahmadi, ,
Volume 23, Issue 2 (3-2019)
Abstract
A simultaneous confidence band gives useful information on the reasonable range of the unknown regression model. In this note, when the predictor variables are constrained to a special ellipsoidal region, hyperbolic and constant width confidence bonds for a multiple linear regression model are compared under the minimum volome confidence set (MVCS) criterion. The size of one speical angle that determines the size of the predictor variable region is used to find out which band is better than the other. When the angle and consquently the size of the predictor variable region is small, the constant width band is better than the hyperbolic band.
When the angle hence the size of the predictor variable regoin is large, the hyperbolic band is considerably better than the constant width band.
Anita Abdollahi Nanvapisheh, ,
Volume 23, Issue 2 (3-2019)
Abstract
In this paper, a new distribution is introduced, which is a generalization of a well-known distribution. This distribution is flexible and applies to income data modeling. We first provide some of the mathematical and distributional properties of this new model and then, to demonstrate the flexibility the new distribution, we will present the applications of this distribution with real data. Data fitting results confirm the appropriateness of this new model for the real data set.
Hamieh Arzhangdamirchi, Reza Pourtaheri,
Volume 23, Issue 2 (3-2019)
Abstract
Many point process models have been proposed for studying variety of scientific disciplines, including geology, medicin, astronomy, forestry, ecology and ect. The assessment of fitting these models is important. Residuals-based methods are appropriate tools for evaluating good fit of spatial point of process models. In this paper, first, the concepts related to the Voronoi residuals are investigated. Then, after fitting a cluster point process to the data set of the position of the trees in the Guilan forest, the proposed model is evaluated using these residuals.
Meysam Yazdani, Firouz Alinia, Mohammad Parsasadr,
Volume 23, Issue 2 (3-2019)
Abstract
The purpose of this study was to determine and evaluate of spatial distribution of gold and silver elements concentration by using geostatistical methods. This study was carried out in Ghezel Ozen area for 95 samples of lithogeochemicals. At first, Censor data was replaced and the values of outlier's data were identified using the box-Plot and Q-Q-Plot charts and reduced by the Doerffel method. Finally, the data were normalized using logarithmic transformations and then the geostatistical analysis was used. Variogram studies showed that the spherical model is the best fitted model and the spatial correlation range for the two elements of Au and Ag were approximately 2500 m. Finally, the estimation and estimation variance maps of the studied elements were prepared by using ordinary kriging geostatistical method with the spherical model on the GS+ software. Evaluating the results by calculating the root mean square error (RMSE) and calculating the mean absolute error (MAE) indicates the acceptable accuracy of variogram model. By studying the kriging estimation and kriging estimation variance maps, the anomal regions were introduced for the elements of Au and Ag in the case study.
Mohamad Hosein Poursaeed,
Volume 23, Issue 2 (3-2019)
Abstract
The censored data are widely used in statistical tests and parameters estimation. In some cases e.g. medical accidents which data are not recorded at the time of occurrence, some methods such as interval censoring are used. In this paper, for a random sample uniformly distributed on the interval (0,θ) the interval censoring have been used. A consistent estimator of θ and some asymptotically confidence intervals for θ are presented.
Aliakbar Rasekhi,
Volume 23, Issue 2 (3-2019)
Abstract
WinBUGS is one of the usual softwares in computational Bayesian statistics, which is used to fit Baysian models easily. Although this software has usual mathematical functions and statistical distributions as built in functions, sometimes it is necessary to include other functions and distributions in computations which is done by some tricks and indirectly. By using WinBUGS development interface (known as WBDev), new mathematical functions and statistical distributions can be added in the software. This method facilitates writing codes of statistical models, increases speed of computations and make computations more efficient. In this paper, the stages of including new mathematical functions and statistical distributions in the WinBUGS are illustrated by some examples.
Ali Shadrokh, Shahrastani Shahram Yaghoobzadeh,
Volume 24, Issue 1 (9-2019)
Abstract
In this study, E-Bayesian and hierarchical Bayesian of parameter of Rayleigh distribution under progressive type-II censoring sampales and the efficiency of the proposed methods has been compared with each and Bayesian estimator using Monte Carlo simulation.
Dr. Mehdi Shams, Dr. Gholamreza Hesamian,
Volume 24, Issue 1 (9-2019)
Abstract
In this paper after introduce Ito integral we discuss filtering problem. In filtering problem there are two stochastic differential equations (system and observation) that given the observations we must find the best estimate for the random process of the system based on these observations. At last we give some useful examples.
Shahrastani Shahram Yaghoobzadeh,
Volume 24, Issue 1 (9-2019)
Abstract
In this paper, reliability in multi-component stress-strength models, when the stress and strength variables are inverse Rayleigh distributions with different parameters of alpha and beta. Estimates of the maximum likelihood, Bayesian and empirical Bayesian are estimated. Then, with the help of Monte Carlo simulation and two real data sets, these estimation methods are compared.
Dr. Shahram Mansouri,
Volume 24, Issue 1 (9-2019)
Abstract
There is a one to one correspondence between renewal function and the probability density function of the times of observations of the successive occurrences of each renewal process. Furthermore, practical application of renewal processes requires renewal function information, and this function plays an essential role in the study of renewal processes behavior by which predictions could be made. In this paper, the renewal functions corresponding with two distributions with the times of successive observations distributed by Erlang (n,lambda) , and uniform (0,b) are determined by Laplace transform and its theorems. Finally, an application of the renewal process is presented in physics.
Ali Bahami, Ebrahim Reyhani, Ehsan Bahami,
Volume 24, Issue 1 (9-2019)
Abstract
The aim of this study, that was carried out in descriptive of the survey, is to assess the understanding and misunderstanding of the concept of probability eighth grade students. The samples of this study are, all eighth grade boy and girl students of Tehran province. The study sample,1330 eighth grade students in Tehran who were selected randomly. A random sample of 1330 students, from different public school. intelligence school, Shahed and perspicacious school randomly classified. and they were given 15 questions. which their validity has been studied by the number of math professors and teachers of mathematics and experienced math teachers. The reliability tests with Cronbach's alpha coefficien. 961 Was confirmed.After analyzing descriptive statistics, misunderstanding of the students were identified in seven groups as follow: lack of understanding rational numbers and its relationship to fractions, lack of understanding some of the concepts prerequisite, language problems, using their own methods to calculate the probability, inability to count all possible states, inappropiate generalization and the inability of the undrestanding of prerequisite problems.
Dr Fatemeh Hosseini, Dr Omid Karimi, Miss Fatemeh Hamedi,
Volume 24, Issue 1 (9-2019)
Abstract
Tree models represent a new and innovative way of analyzing large data sets by dividing predictor space into simpler areas. Bayesian Additive Regression Trees model, a model that we explain in this article, uses a totality of trees in its structure, since the combination of several trees from a tree only has a higher accuracy.
Then, this model is a tree-based model and a nonparametric model that uses general aggregation methods, and boosting algorithms in particular and in fact is extension of the classification and Regression Tree methods in which the decision tree exists in the structure of these methods.
In this method, on the parameters of the model sum of tree and put regular prior then use the boosting algorithms for analysis. In this paper, first the Bayesian Additive Regression Trees model is introduced and then applied in survival analysis of lung cancer patients.
Saeed Zhlzadeh, Sima Zamani,
Volume 24, Issue 1 (9-2019)
Abstract
Consider a coherent system consisting of independent or dependent components and assume that the components are randomly chosen from two different batches, where the components lifetimes of the first batch are larger than those of the second in some stochastic order sense. In this paper, using different stochastic orders, we compare the reliability of such systems and show that the reliability of the systems increases, as the random number of components chosen from the first batch increases in different stochastics orders. We use copula function to describe dependence structure between component lifetimes.
Ma , ,
Volume 24, Issue 1 (9-2019)
Abstract
One of the most common reasons of corneal transplantation in Iran is Keratoconus. Keratoconus is a non-inflammatory phenomenon which usually affects the cornea of both eyes. Since in corneal transplantation a portion of people may not reject the transplanted organ so for studying the effective factors on survival time of these data , the survival analysis with cure ratio was used.
Mohammad Jafari Aminabadi, Javid Jowzadani, Hadi Shiroyeh Zad, Khalegh Behrooz Dehkordi,
Volume 24, Issue 1 (9-2019)
Abstract
Regard to daily increasing of customer services share in all over the world, one of most effective parameters on customer satisfaction would be service delivery with the least delay. work allocation method, planning, organizing, prioritizing and service delivery routing have always been one of the main concerns of service providing centers and lack of proper planning in this regard will cause service network traffic, environmental and noise pollution, waste of time and fuel and eventually dissatisfaction of consumers and technicians.
On the other hand, daily division of labor in order to deliver delightful services by considering man’s opinion would not be an optimal choice. In this research, with case study on a home appliance service company and by considering customer demands in city of Isfahan and by data analysis, geographic points of customer’s demands have clustered by k-mean algorithm.
It has been tried to reduce the search space by clustering geographic areas and then by using simulated annealing, the optimum path for customer’s probable demands present to the technicians with observance of daily working capacity per cluster.
The computational results show that after clustering by k-means algorithm, routing probable demands with observance of daily working capacity for technicians, the objective function has better improvement in compare with non-clustering case.
Service technician routing by clustering, while being responsive in shortest time, has more repeatability test and cause more order and responsibility sense and more domination on service areas and also has an effective role in reducing time to handle a consumer and getting their satisfaction.
Seyedeh Mona Ehsani Jokandan, Behrouz Fathi Vajargah,
Volume 24, Issue 2 (3-2020)
Abstract
In this paper, the difference between classical regression and fuzzy regression is discussed. In fuzzy regression, nonphase and fuzzy data can be used for modeling. While in classical regression only non-fuzzy data is used.
The purpose of the study is to investigate the possibility of regression method, least squares regression based on regression and linear least squares linear regression method based on fuzzy weight calculation for non-fuzzy input and fuzzy output using symmetric triangular fuzzy numbers. Further reliability, confidence intervals and fitness fit criterion is presented for choosing the optimal model.
Finally, by providing examples of the behavior of the proposed methods, the optimality of the regression hybrid model is shown by the least linear fuzzy squares.
Akram Heidari Garmianaki, Mehrdad Niaparast,
Volume 24, Issue 2 (3-2020)
Abstract
In the present era, classification of data is one of the most important issues in various sciences in order to
detect and predict events. In statistics, the traditional view of these classifications will be based on classic
methods and statistical models such as logistic regression. In the present era, known as the era of explosion
of information, in most cases, we are faced with data that cannot find the exact distribution. Therefore, the
use of data mining and machine learning methods that do not require predetermined models can be useful.
In many countries, the exact identification of the type of groundwater resources is one of the important
issues in the field of water science. In this paper, the results of the classification of a data set for groundwater resources were compared using regression, neural network, and support vector machine.
The results of these classifications showed that machine learning methods were effective in determining the exact type of springs.
, ,
Volume 24, Issue 2 (3-2020)
Abstract
The minimum density power divergence method provides a robust estimate in the face of a situation where the dataset includes a number of outlier data.
In this study, we introduce and use a robust minimum density power divergence estimator to estimate the parameters of the linear regression model and then with some numerical examples of linear regression model, we show the robustness of this estimator in the face of a dataset which includes a number of outliers.
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