Statistical Computing
Hassan Rashidi; Hamed Heidari; Marzie Movahedin; Maryam Moazami Gudarzi; Mostafa Shakerian
Abstract
The purpose of this research is to identify and introduce effective factors in adoption of e-learning based on technology adoption model. Accordingly, by considering the studies conducted in this field, several variables such as computer self-efficacy, content quality, system support, interface design, ...
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The purpose of this research is to identify and introduce effective factors in adoption of e-learning based on technology adoption model. Accordingly, by considering the studies conducted in this field, several variables such as computer self-efficacy, content quality, system support, interface design, technology tools and computer anxiety as factors influencing the adoption of e-learning system were extracted and based on them, a conceptual model of research was developed. To measure the model and the relationships between the variables in the model, a questionnaire was designed and provided to users of the electronic education system of Qazvin University of Medical Sciences. The results of the data analysis confirmed the correctness of all hypotheses using the structural equation modeling method, except for the effect of technology tools on the acceptance of the e-learning system. The findings of this study will help university administrators and the professors associated with this system to encourage students to make effective use of the system by creating the necessary background for effective factors.
Statistical Computing
farzad eskandari
Abstract
Interval-valued data are observed as ranges instead of single values and contain richer information thansingle-valued data. Meanwhile, interval-valued data are used for interval-valued characteristics. An intervalgeneralized linear model is proposed for the first time in this research. Then a suitable ...
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Interval-valued data are observed as ranges instead of single values and contain richer information thansingle-valued data. Meanwhile, interval-valued data are used for interval-valued characteristics. An intervalgeneralized linear model is proposed for the first time in this research. Then a suitable model is presented toestimate the parameters of the interval generalized linear model. The two models are provided on the basis ofthe interval arithmetic. The estimation procedure of the parameters of the suitable model is as the estimationprocedure of the parameters of the interval generalized linear model. The least-squares (LS) estimation of thesuitable model is developed according to a nice distance in the interval space. The LS estimation is resolvedanalytically through a constrained minimization problem. Then some desirable properties of the estimatorsare checked. Finally, both the theoretical and the empirical performance of the estimators are investigated.
Statistical Computing
Raheleh Zamini
Abstract
In various statistical model, such as density estimation and estimation of regression curves or hazardrates, monotonicity constraints can arise naturally. A frequently encountered problem in nonparametricstatistics is to estimate a monotone density function f on a compact interval. A known estimator ...
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In various statistical model, such as density estimation and estimation of regression curves or hazardrates, monotonicity constraints can arise naturally. A frequently encountered problem in nonparametricstatistics is to estimate a monotone density function f on a compact interval. A known estimator fordensity function of f under the restriction that f is decreasing, is Grenander estimator, where is the leftderivative of the least concave majorant of the empirical distribution function of the data. Many authorsworked on this estimator and obtained very useful properties from this estimator. Grenander estimatoris a step function and as a consequence it is not smooth. In this paper, we discuss the estimation of adecreasing density function by the kernel smoothing method. Many works have been done due to theimportance and applicability of Berry-Esseen bounds for the density estimator. In this paper, we studya Berry- Esseen type bound for a smoothed version of Grenander estimator.
Statistical Computing
Abstract
This paper presents approximate confidence intervals for each function of parameters in a Banach space based on a bootstrap algorithm. We apply kernel density approach to estimate the persistence landscape. In addition, we evaluate the quality distribution function estimator of random variables ...
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This paper presents approximate confidence intervals for each function of parameters in a Banach space based on a bootstrap algorithm. We apply kernel density approach to estimate the persistence landscape. In addition, we evaluate the quality distribution function estimator of random variables using integrated mean square error (IMSE). The results of simulation studies show a significant improvement achieved by our approach compared to the standard version of confidence intervals algorithm. Finally, real data analysis shows that the accuracy of our method compared to that of previous works for computing the confidence interval.
Statistical Computing
mohammad hossein naderi; Mohammad Bameni Moghadam; asghar Seif
Abstract
A proper method of monitoring a stochastic system is to use the control charts of statisticalprocess control in which a drift in characteristics of output may be due to one or several assignable causes. In the establishment of X charts in statistical process control, an assumption is made that there ...
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A proper method of monitoring a stochastic system is to use the control charts of statisticalprocess control in which a drift in characteristics of output may be due to one or several assignable causes. In the establishment of X charts in statistical process control, an assumption is made that there is no correlation within the samples. However, in practice, there are many cases where the correlation does exist within the samples. It would be more appropriate to assume that each sample is a realization of a multivariatenormal random vector. Using three di erent loss functions in the concept of quality control charts with economic and economic statistical design leads to better decisions in the industry. Although some research works have considered the economic design of control charts under single assignable cause and correlated data, the economic statistical design of X control chart for multiple assignable causes and correlated data under Weibull shock model with three di erent loss functions have not been presented yet. Based on theoptimization of the average cost per unit of time and taking into account the di erent combination valuesof Weibull distribution parameters, optimal design values of sample size, sampling interval and control limitcoecient were derived and calculated. Then the cost models under non-uniform and uniform samplingscheme were compared. The results revealed that the model under multiple assignable causes with correlatedsamples with non-uniform sampling integrated with three di erent loss functions has a lower cost than themodel with uniform sampling.
