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Showing 9 results for jafari
A.a Jafari,
Volume 13, Issue 2 (3-2009)
Abstract
Student Atefe Javidi, Student Somayeh Rahpeima, Dr Majid Jafari Khaledi,
Volume 18, Issue 2 (3-2014)
Abstract
Statistical models are utilized to learn about the mechanism that the data are generating from it. Often it is assumed that the random variables y_i,i=1,…,n ,are samples from the probability distribution F which is belong to a parametric distributions class. However, in practice, a parametric model may be inappropriate to describe the data. In this settings, the parametric assumption could be relaxed and more flexible models could be used analysis of data. In the nonparametric Bayes approach, a prior distributions is defined over the whole space of probability distributions for random variable distribution. Due to the Dirichlet process (DP) has interesting properties, it is thus used extensively. In this paper, we introduce DP and its features.
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.
Hamid Reza Nili Sani, Mehdi Jafari,
Volume 25, Issue 2 (3-2021)
Abstract
In this study, we first introduce the Banach lattice random elements and some of their properties. Then, using the order defined in Banach lattice space, we introduce and characterize the order negatively dependence Banach lattice random elements by the order defined in Banach lattice space. Finally, we obtain some limit theorems for the sequence of order negatively dependence Banach lattice random elements.
Dr Mahdi Roozbeh, Ms mlihe Malekjafarian, Ms Monireh Maanavi,
Volume 26, Issue 2 (3-2022)
Abstract
The most important goal of statistical science is to analyze the real data of the world around us. If this information is analyzed accurately and correctly, the results will help us in many important decisions. Among the real data around us which its analysis is very important, is the water consumption data. Considering that Iran is located in a semi-arid climate area of the earth, it is necessary to take big steps for predicting and selecting the best and the most appropriate accurate models of water consumption, which is necessary for the macro-national decisions. But analyzing the real data is usually complicated. In the analysis of the real data set, we usually encounter with the problems of multicollinearity and outliers points. Robust methods are used for analyzing the datasets with outliers and ridge method is used for analyzing the data sets with multicollinearity. Also, the restriction on the models is resulted from using non-sample information in estimation of regression coefficients. In this paper, it is proceeded to model the water consumption data using robust stochastic restricted ridge approach and then, the performance of the proposed method is examined through a Monte Carlo simulation study.
Dr Majid Jafari Khaledi, Mr Hassan Mirzavand,
Volume 26, Issue 2 (3-2022)
Abstract
To make statistical inferences about regression model parameters, it is necessary to assume a specific distribution on the random error expression. A basic assumption in a linear regression model is that the random error expression follows a normal distribution. However, in some statistical researches, data simultaneously display skewness and bimodality features. In this setting, the normality assumption is violated. A common approach to avoiding this problem is to use a mixture of skew-normal distributions. But such models involve many parameters, which it makes difficult to fit the models to the data. Moreover, these models are faced with the non-identifiability issue.
In this situation, a suitable solution is to use flexible distributions, which can take into account the skewness and bimodality observed in the data distribution. In this direction, various methods have been proposed based on developing of the skew-normal distribution in recent years. In this paper, these methods are used to introduce more flexible regression models than the regression models based on skew-normal distribution and a mixture of two skew-normal distributions. Their performance is compared using a simulation example. The methodology is then illustrated in a practical example related to a horses dataset.
Habib Jafari, Anita Abdollahi,
Volume 27, Issue 1 (3-2023)
Abstract
Anthropometr is a science that deals with the size of the body including the dimensions of different parts, the field of motion and the strength of the muscles of the body. Specific individual dimensions such as heights, widths, depths, distances, environments and curvatures are usually measured. In this article, we investigate the anthropometric characteristics of patients with chronic diseases (diabetes, hypertension, cardiovascular disease, heart attacks and strokes) and find the factors affecting these diseases and the extent of the impact of each to make the necessary planning.
This research is done descriptively-analytically, the research community of the people of Ravansar county is one of the functions of Kermanshah province. MATLAB, R and SPSS statistical software are used to analyze the data and test the presented hypotheses. Significance level for all tests is less than 0.05. Descriptive statistics methods is used to describe and summarize the variables. The Pearson correlation analysis method is used to investigate the relationship between variables, regression analysis (logistics) is used to investigate the effect of independent variables on the dependent variable. According to the results, it seems that some anthropometric indicators have a significant relationship with risk factors of chronic diseases. So, continuous evaluations, lifestyle changes and increasing the level of awareness to control, prevent and adjust the indicators are suggested.
Ms. Zahra Jafarian Moorakani, Dr. Heydar Ali Mardani-Fard,
Volume 27, Issue 1 (3-2023)
Abstract
The ordinary linear regression model is $Y=Xbeta+varepsilon$ and the estimation of parameter $beta$ is: $hatbeta=(X'X)^{-1}X'Y$. However, when using this estimator in a practical way, certain problems may arise such as variable selection, collinearity, high dimensionality, dimension reduction, and measurement error, which makes it difficult to use the above estimator. In most of these cases, the main problem is the singularity of the matrix $X'X$. Many solutions have been proposed to solve them. In this article, while reviewing these problems, a set of common solutions as well as some special and advanced methods (which are less favored by someone, but still have the potential to solve these problems intelligently) to solve them.
Shahrastani Shahram Yaghoobzadeh Shahrastani, Amrollah Jafari,
Volume 28, Issue 1 (9-2023)
Abstract
In this article, queunig model $M/M/1$ is Considered, in which the innterarrival of customers have an exponenial disributon with the parameter $lambda$ and the service times have an exponenial disributon with the parameter $mu$ and are independent of the interarrival times. it is also assumed that the system is active until $T$. Then, under this stopping time Bayesian, $E$-Bayesian and hierarchical Bayesian estimations of the traffic intensity parameter of this queuing model are obtained under the general entropy loss function and considering the gamma and erlang prior distributions for parameters $lambda$ and $mu$, respicctively. Then, using numerical analysis and based on a new index, Bayesian, $E$-Bayesian and hierarchical Bayesian estimations are compared.
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