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Articles 121 - 150 of 161
Full-Text Articles in Statistics and Probability
Strong Uniform Consistency Of Hazard Function With Functional Explicatory Variable In Single Functional Index Model Under Censored Data, Omar Belabbaci, Abbes Rabhi, Sara Soltani
Strong Uniform Consistency Of Hazard Function With Functional Explicatory Variable In Single Functional Index Model Under Censored Data, Omar Belabbaci, Abbes Rabhi, Sara Soltani
Applications and Applied Mathematics: An International Journal (AAM)
In this paper we deal with nonparametric estimate of the conditional hazard function, when the covariate is functional. Kernel type estimators for the conditional hazard function of a scalar response variable Y given a Hilbertian random variable X are introduced, where the observations are linked with a single-index structure. We establish the pointwise almost complete convergence and the uniform almost complete convergence (with the rate) of the kernel estimate of this model in various situations, including censored and non-censored data. The rates of convergence emphasize the crucial role played by the small ball probabilities with respect to the distribution of …
Estimation Of The Parameters Of Exponential Distribution Using Top-K-Lists, M. Ahsanullah, Mohamed Habibullah
Estimation Of The Parameters Of Exponential Distribution Using Top-K-Lists, M. Ahsanullah, Mohamed Habibullah
Applications and Applied Mathematics: An International Journal (AAM)
This paper deals with the estimation of location and scale parameters of the exponential distribution based on top-k-list of a sequence of observations from a two parameter exponential distribution. The minimum variance unbiased estimates of the location and scale parameters are given. Some comparisons of the variances of these estimates with respect to that of the kth record values are given.
Analysis Of Repairable M[X]/(G1,G2)/1 - Feedback Retrial G-Queue With Balking And Starting Failures Under At Most J Vacations, P. Rajadurai, M. C. Saravanarajan, V. M. Chandrasekaran
Analysis Of Repairable M[X]/(G1,G2)/1 - Feedback Retrial G-Queue With Balking And Starting Failures Under At Most J Vacations, P. Rajadurai, M. C. Saravanarajan, V. M. Chandrasekaran
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, we discuss the steady state analysis of a batch arrival feedback retrial queue with two types of services and negative customers. Any arriving batch of positive customers finds the server is free, one of the customers from the batch enters into the service area and the rest of them get into the orbit. The negative customer, is arriving during the service time of a positive customer, will remove the positive customer in-service and the interrupted positive customer either enters the orbit or leaves the system. If the orbit is empty at the service completion of each type …
Testing Equality Of Locally Stationary Covariances With Application To Mortality Rate Modeling, Zahra Teimouri, Ali R. Taheriyoun
Testing Equality Of Locally Stationary Covariances With Application To Mortality Rate Modeling, Zahra Teimouri, Ali R. Taheriyoun
Applications and Applied Mathematics: An International Journal (AAM)
No abstract provided.
Sensitivity Analysis In Correlated Bivariate Continuous And Binary Responses, Zh. Thmasebinejad, E. Tabrizi
Sensitivity Analysis In Correlated Bivariate Continuous And Binary Responses, Zh. Thmasebinejad, E. Tabrizi
Applications and Applied Mathematics: An International Journal (AAM)
Factorization models for correlated binary and continuous responses are proposed. Full likelihood-based approach that yields maximum likelihood estimates of the model parameters is used. A common way to investigate if perturbations of model components influence key results of the analysis is to compare the results derived from the original and perturbed models using an influence graph. So small perturbation influence of the correlation parameters of the models on likelihood displacement and a general index of sensitivity (ISNI) are also studied. The model is illustrated using data from arthritis and body mass index data. The effect of systolic blood pressure, gender …
A Semi-Parametric Approach For Analyzing Longitudinal Measurements With Non-Ignorable Missingness Using Regression Spline, Taban Baghfalaki, Saeide Sefidi, Mojtaba Ganjali
A Semi-Parametric Approach For Analyzing Longitudinal Measurements With Non-Ignorable Missingness Using Regression Spline, Taban Baghfalaki, Saeide Sefidi, Mojtaba Ganjali
Applications and Applied Mathematics: An International Journal (AAM)
In longitudinal studies with missingness, shared parameter models (SPM) provide appropriate framework for the joint modeling of the measurements and missingness process. These models use a set of random effects to account for the interdependence between two processes. Sometimes the longitudinal responses may not be fitted well by using a linear model and some non-parametric methods have to be used. Also, parametric assumptions are typically made for the random effects distribution, and violation of those may affect the parameter estimates and standard errors. To overcome these problems, we propose a semi-parametric model for the joint modelling of longitudinal markers and …
Outlier Detection And A Method Of Adjustment For The Iranian Manufacturing Establishment Survey Data, Zahra R. Ghahroodi, Taban Baghfalaki, Mojtaba Ganjali
Outlier Detection And A Method Of Adjustment For The Iranian Manufacturing Establishment Survey Data, Zahra R. Ghahroodi, Taban Baghfalaki, Mojtaba Ganjali
Applications and Applied Mathematics: An International Journal (AAM)
The role and importance of the industrial sector in the economic development necessitate the need to collect and to analyze accurate and timely data for exact planning. As the occurrence of outliers in establishment surveys are common due to the structure of the economy, the evaluation of survey data by identifying and investigating outliers, prior to the release of data, is necessary. In this paper, different robust multivariate outlier detection methods based on the Mahalanobis distance with blocked adaptive computationally efficient outlier nominators algorithm, minimum volume ellipsoid estimator, minimum covariance determinant estimator and Stahel-Donoho estimator are used in the context …
Gaussian Copula Mixed Models With Non-Ignorable Missing Outcomes, N. Jafari, E. Tabrizi, E. B. Samani
Gaussian Copula Mixed Models With Non-Ignorable Missing Outcomes, N. Jafari, E. Tabrizi, E. B. Samani
Applications and Applied Mathematics: An International Journal (AAM)
This paper is concerned with the analysis of mixed data with ordinal and continuous outcomes with the possibility of non - ignorable missing outcomes . A copula-based regression model is proposed that accounts for associations between ordinal and continuous outcomes . Our approach entails specifying underlying latent variables for the mixed outcomes to indicate the latent mechanisms which generate the ordinal and continuous variables . Maximum likelihood estimation of our model parameters is implemented using standard software such as function nlminb in R . Results of simulations concern the relative biases of parameter estimates of joint and marginal models using …
Exponential Type Product Estimator For Finite Population Mean With Information On Auxiliary Attribute, Monika Saini, Ashish Kumar
Exponential Type Product Estimator For Finite Population Mean With Information On Auxiliary Attribute, Monika Saini, Ashish Kumar
Applications and Applied Mathematics: An International Journal (AAM)
The main objective of the present study is to develop a new modified unbiased exponential type product estimator for the estimation of the population mean. The proposed estimator possesses the characteristic of a bi-serial negative correlation between the study variable and its auxiliary attribute. Efficiency comparison has been carried out between the proposed estimator and the existing estimators theoretically and numerically.
A Semiparametric Estimation For Regression Functions In The Partially Linear Autoregressive Time Series Model, R. Farnoosh, M. Hajebi, S. J. Mortazavi
A Semiparametric Estimation For Regression Functions In The Partially Linear Autoregressive Time Series Model, R. Farnoosh, M. Hajebi, S. J. Mortazavi
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, a semiparametric method is proposed for estimating regression function in the partially linear autoregressive time series model . Here, we consider a combination of parametric forms and nonlinear functions, in which the errors are independent. Semiparametric and nonparametric curve estimation provides a useful tool for exploring and understanding the structure of a nonlinear time series data set to make for a more efficient study in the partially linear autoregressive model. The unknown parameters are estimated using the conditional nonlinear least squares method, and the nonparametric adjustment is also estimated by defining and minimizing the local L2 -fitting …
A Likelihood Ratio Test Approach To Profile Monitoring In Tourism Industry, R. Noorossana, H. Izadbakhsh, M. R. Nayebpour
A Likelihood Ratio Test Approach To Profile Monitoring In Tourism Industry, R. Noorossana, H. Izadbakhsh, M. R. Nayebpour
Applications and Applied Mathematics: An International Journal (AAM)
A new statistical profile monitoring technique to monitor and detect changes in logistic profiles with an application in the tourism industry is presented in this paper. In the statistical process control literature, profile is usually referred to as a relationship between a response variable and one or more explanatory variables. In the tourism case study presented in this paper, time is considered as the explanatory variable and tourism satisfaction as the response variable. The Likelihood ratio test is used as a vehicle to detect any changes in the satisfaction profile in phase II of profile monitoring. The performance of the …
A New Adjustment Of Laplace Transform For Fractional Bloch Equation In Nmr Flow, Sunil Kumar, Devendra Kumar, U. S. Mahabaleshwar
A New Adjustment Of Laplace Transform For Fractional Bloch Equation In Nmr Flow, Sunil Kumar, Devendra Kumar, U. S. Mahabaleshwar
Applications and Applied Mathematics: An International Journal (AAM)
This work purpose suggest a new analytical technique called the fractional homotopy analysis transform method (FHATM) for solving time fractional Bloch NMR (nuclear magnetic resonance) flow equations, which are a set of macroscopic equations that are used for modeling nuclear magnetization as a function of time. The true beauty of this article is the coupling of the homotopy analysis method and the Laplace transform method for systems of fractional differential equations. The solutions obtained by the proposed method indicate that the approach is easy to implement and computationally very attractive.
A Characterization Of Skew Normal Distribution By Truncated Moment, M. Shakil, M. M. Ahsanullah, B. M. Golam Kibria
A Characterization Of Skew Normal Distribution By Truncated Moment, M. Shakil, M. M. Ahsanullah, B. M. Golam Kibria
Applications and Applied Mathematics: An International Journal (AAM)
A probability distribution can be characterized through various methods. This paper discusses a new characterization of skew normal distribution by truncated moment. It is hoped that the findings of the paper will be useful for researchers in different fields of applied sciences
Stochastic Modeling Of A Concrete Mixture Plant With Preventive Maintenance, Ashish Kumar, Monika Saini, S. C. Malik
Stochastic Modeling Of A Concrete Mixture Plant With Preventive Maintenance, Ashish Kumar, Monika Saini, S. C. Malik
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, a stochastic model for concrete mixture plant with Preventive Maintenance (PM) is analyzed in detail by using a supplementary variable technique. In a concrete mixture plant eight subsystems are arranged in a series. The system goes under PM after a maximum operation time and work as new after PM. The time to failure of each subsystem follows a negative exponential distribution while PM and repair time distributions are taken as arbitrary. A sufficient repair facility is provided to the system for conducting PM and repair of the system. Repair, maintenance and switch devices are perfect. All random …
Acceptance Sampling Plans For Percentiles Based On The Exponentiated Half Logistic Distribution, G. S. Rao, Ch. R. Naidu
Acceptance Sampling Plans For Percentiles Based On The Exponentiated Half Logistic Distribution, G. S. Rao, Ch. R. Naidu
Applications and Applied Mathematics: An International Journal (AAM)
In this article, acceptance sampling plans are developed for the exponentiated half logistic distribution percentiles when the life test is truncated at a pre-specified time. The minimum sample size necessary to ensure the specified life percentile is obtained under a given customer’s risk. The operating characteristic values (and curves) of the sampling plans as well as the producer’s risk are presented. Two examples with real data sets are also given as illustration.
A Ranking Method Based On Common Weights And Benchmark Point, Ali Payan, Abbas A. Noora, Farhad H. Lotfi
A Ranking Method Based On Common Weights And Benchmark Point, Ali Payan, Abbas A. Noora, Farhad H. Lotfi
Applications and Applied Mathematics: An International Journal (AAM)
The highest efficiency score 1 (100% efficiency) is regarded as a common benchmark for Decision Making Units (DMUs). This brings about the existence of more than one DMU with the highest score. Such a case normally occurs in all Data Envelopment Analysis (DEA) models and also in all the Common Set of Weights (CSWs) methods and it may lead to the lack of thorough ranking of DMUs. And ideal DMU based on its specific structure is a unit that no unit would do better than. Therefore, it can be utilized as a benchmark for other units. We are going to …
Application Of Fractional Moments For Comparing Random Variables With Varying Probability Distributions, Munther R. Al Shami, A. R. Mugdadi, R. R. Nigmatullin, S. I. Osokin
Application Of Fractional Moments For Comparing Random Variables With Varying Probability Distributions, Munther R. Al Shami, A. R. Mugdadi, R. R. Nigmatullin, S. I. Osokin
Applications and Applied Mathematics: An International Journal (AAM)
New methods are being presented for statistical treatment of different random variables with unknown probability distributions. These include analysis based on the probability circles, probability ellipses, generalized mean values, generalized Pearson correlation coefficient and the beta-function analysis. Unlike other conventional statistical procedures, the main distinctive feature of these new methods is that no assumptions are made about the nature of the probability distribution of the random series being evaluated. Furthermore, the suggested procedures do not introduce uncontrollable errors during their application. The effectiveness of these methods is demonstrated on simulated data with extended and reduced sample sizes having different probability …
Analysis Of Mixed Correlated Bivariate Negative Binomial And Continuous Responses, F. Razie, E. B. Samani, M. Ganjali
Analysis Of Mixed Correlated Bivariate Negative Binomial And Continuous Responses, F. Razie, E. B. Samani, M. Ganjali
Applications and Applied Mathematics: An International Journal (AAM)
A general model for the mixed correlated negative binomial and continuous responses is proposed. It is shown how to construct parameter of the models, using the maximization of the full likelihood. Influence of a small perturbation of correlation parameter of the model on the likelihood displacement is also studied. The model is applied to a medical data, obtained from an observational study on women, where the correlated responses are the negative binomial response of joint damage and continuous responses of body mass index. Simultaneous effects of some covariates on both responses are investigated.
Certain Fractional Integral Operators And The Generalized Incomplete Hypergeometric Functions, H. M. Srivastava, Praveen Agarwal
Certain Fractional Integral Operators And The Generalized Incomplete Hypergeometric Functions, H. M. Srivastava, Praveen Agarwal
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, we apply a certain general pair of operators of fractional integration involving Appell’s function F3 in their kernel to the generalized incomplete hypergeometric functions pΓq[z] and pɣq [z], which were introduced and studied systematically by Srivastava et al. in the year 2012. Some interesting special cases and consequences of our main results are also considered.
The Mx/G/1 Queue With Unreliable Server, Delayed Repairs, And Bernoulli Vacation Schedule Under T-Policy, L. Tadj, G. Choudhury
The Mx/G/1 Queue With Unreliable Server, Delayed Repairs, And Bernoulli Vacation Schedule Under T-Policy, L. Tadj, G. Choudhury
Applications and Applied Mathematics: An International Journal (AAM)
In this paper we study a batch arrival queuing system. The server may break down while delivering service. However, repair is not provided immediately, rather it is delayed for a random amount of time. At the end of service, the server may process the next customer if any are available, or may take a vacation to execute some other job. Finally, the server implements the T-policy. We describe for this system an optimal management policy. Numerical examples are provided.
Using Fuzzy Linear Regression To Estimate Relationship Between Forest Fires And Meteorological Conditions, Hande G. Akdemir, Fatma Tiryaki
Using Fuzzy Linear Regression To Estimate Relationship Between Forest Fires And Meteorological Conditions, Hande G. Akdemir, Fatma Tiryaki
Applications and Applied Mathematics: An International Journal (AAM)
Each year, millions of hectares of forest land are destroyed by fires causing great financial loss and ecological damage. In this paper, our aim is to study the effect of the variation of meteorological conditions on the total burned area in hectares, by using fuzzy linear regression analysis based on Tanaka’s approaches. The total burned area is considered a dependent variable. Air temperature (in ºC), relative humidity (in %), wind speed (in km/h) and rainfall (in mm/m2 ) are considered to be independent variables. The relationship between input and output data is estimated using data provided in data mining …
Local Influence In Bayesian Elliptically Contoured-Ordinal Model For Mixed Data, Ehsan B. Samani
Local Influence In Bayesian Elliptically Contoured-Ordinal Model For Mixed Data, Ehsan B. Samani
Applications and Applied Mathematics: An International Journal (AAM)
This paper develops a new class of joint modeling of mixed correlated ordinal and continuous responses with elliptically contoured errors. This joint model includes the latent variable approach of using an elliptically contoured distribution for mixed ordinal and continuous responses. A Markov Chain Monte Carlo sampling algorithm is described for estimating the posterior distribution of the parameters. For sensitivity analysis to investigate the perturbation from associate responses, it is demonstrated how one can use some elements of covariance structure. Influence of small perturbation of these elements on the posterior normal curvature is also studied. To illustrate the application of such …
Study Of Reliability With Mixed Standby Components, M. A. El-Damcese, A. N. Helmy
Study Of Reliability With Mixed Standby Components, M. A. El-Damcese, A. N. Helmy
Applications and Applied Mathematics: An International Journal (AAM)
This paper deals with the reliability characteristics of two different series system configurations with mixed standby (include cold and warm standby) components. The failure rates of the primary and warm standby components are assumed to follow the Weibull distribution. The repair time distribution of each server is exponentially distributed. Moreover, we will derive the mean time-to-failure, and the steady-state availability for a special case of a serial system of two primary components, two warm standby components, and one cold standby component, when the failure and repair rate are constant.
Distributional Properties Of Record Values Of The Ratio Of Independent Exponential And Gamma Random Variables, M. Shakil, M. Ahsanullah
Distributional Properties Of Record Values Of The Ratio Of Independent Exponential And Gamma Random Variables, M. Shakil, M. Ahsanullah
Applications and Applied Mathematics: An International Journal (AAM)
Both exponential and gamma distributions play pivotal roles in the study of records because of their wide applicability in the modeling and analysis of life time data in various fields of applied sciences. In this paper, a distribution of record values of the ratio of independent exponential and gamma random variables is presented. The expressions for the cumulative distribution functions, moments, hazard function and Shannon entropy have been derived. The maximum likelihood, method of moments and minimum variance linear unbiased estimators of the parameters, using record values and the expressions to calculate the best linear unbiased predictor of record values, …
A Stochastic Version Of The Em Algorithm To Analyze Multivariate Skew-Normal Data With Missing Responses, M. Khounsiavash, M. Ganjali, T. Baghfalaki
A Stochastic Version Of The Em Algorithm To Analyze Multivariate Skew-Normal Data With Missing Responses, M. Khounsiavash, M. Ganjali, T. Baghfalaki
Applications and Applied Mathematics: An International Journal (AAM)
In this paper an algorithm called SEM, which is a stochastic version of the EM algorithm, is used to analyze multivariate skew-normal data with intermittent missing values. Also, a multivariate selection model framework for modeling of both missing and response mechanisms is formulated. By the SEM algorithm missing values of responses are inputed by the conditional distribution of missing values given observed data and then the log-likelihood of the pseudocomplete data is maximized. The algorithm is iterated until convergence of parameter estimates. Results of an application are also reported where a Bootstrap approach is used to compute the standard error …
Applying Gmdh-Type Neural Network And Genetic Algorithm For Stock Price Prediction Of Iranian Cement Sector, Saeed Fallahi, Meysam Shaverdi, Vahab Bashiri
Applying Gmdh-Type Neural Network And Genetic Algorithm For Stock Price Prediction Of Iranian Cement Sector, Saeed Fallahi, Meysam Shaverdi, Vahab Bashiri
Applications and Applied Mathematics: An International Journal (AAM)
The cement industry is one of the most important and profitable industries in Iran and great content of financial resources are investing in this sector yearly. In this paper a GMDH-type neural network and genetic algorithm is developed for stock price prediction of cement sector. For stocks price prediction by GMDH type-neural network, we are using earnings per share (EPS), Prediction Earnings Per Share (PEPS), Dividend per share (DPS), Price-earnings ratio (P/E), Earnings-price ratio (E/P) as input data and stock price as output data. For this work, data of ten cement companies is gathering from Tehran stock exchange (TSE) in …
A Group Acceptance Sampling Plans For Lifetimes Following A Marshall-Olkin Extended Exponential Distribution, G. S. Rao
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, a group acceptance sampling plan is developed for a truncated life test when the lifetime of an item follows the Marshall-Olkin extended exponential distribution. The minimum number of groups required for a given group size and the acceptance number is determined when the consumer’s risk and the test termination time are specified. The operating characteristic values, according to various quality levels, are found and the minimum ratios of the true average life to the specified life at the specified producer’s risk are obtained. The results are explained with examples.
A Multivariate Variable Model With Possibility Of Missing Data On A Stochastic Process, Ehsan B. Samani
A Multivariate Variable Model With Possibility Of Missing Data On A Stochastic Process, Ehsan B. Samani
Applications and Applied Mathematics: An International Journal (AAM)
A joint model for multivariate responses with potentially non-random missing values on a stochastic process is proposed. A full likelihood-based approach that allows yielding maximum likelihood estimates of the model parameters is used. Sensitivity of the results to the assumptions is also investigated. A common way to investigate whether perturbations of model components influence key results of the analysis is to compare the results derived from the original and perturbed models using a general index of sensitivity (ISNI). The approach is illustrated by analyzing a finance data set.
Empirical Comparison Of Some Test Statistics For Testing The Mean Of A Poisson Distribution, B. M. Golam Kibria, Florence George
Empirical Comparison Of Some Test Statistics For Testing The Mean Of A Poisson Distribution, B. M. Golam Kibria, Florence George
Applications and Applied Mathematics: An International Journal (AAM)
This paper considers the problem of hypotheses testing of the mean of a Poisson distribution. Accordingly we consider the following test statistics: Wald, WCC, Score (S), FT, VS, RVS, Exact and Bayes test statistics. A simulation study based on both one and two sided alternatives has been conducted to compare the performances of the test statistics. The study suggests that for a large sample size, all proposed test statistics except VCC and FT perform well in the sense of correct type I error rate of the test and power. However, for a small sample size, Score and VS have better …
Concomitants Of Upper Record Statistics For Bivariate Pseudo–Weibull Distribution, Muhammad Ahsanullah, Saman Shahbaz, Muhammad Qaiser Shahbaz, Muhammad Mohsin
Concomitants Of Upper Record Statistics For Bivariate Pseudo–Weibull Distribution, Muhammad Ahsanullah, Saman Shahbaz, Muhammad Qaiser Shahbaz, Muhammad Mohsin
Applications and Applied Mathematics: An International Journal (AAM)
In this paper the Bivariate Pseudo–Weibull distribution has been defined as a compound distribution of two random variables to model the failure rate of component reliability. The distribution of r–th concomitant and joint distribution of r–th and s–th concomitant of record statistics of the resulting distribution have been derived. Single and product moments alongside the correlation coefficient have also been obtained. Recurrence relation for the single moments has also been obtained for the resulting distributions.