Browsing by Author "Rao, Gadde Srinivasa"

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    A new cosine-originated probability distribution with symmetrical and asymmetrical behaviors: repetitive acceptance sampling with reliability application
    (MDPI AG, 2023) Alshanbari, Huda M.; Rao, Gadde Srinivasa; Seong, Jin-Taek; Salem, Sultan; Khosa, Saima K.
    Several new acceptance sampling plans using various probability distribution methods have been developed in the literature. However, there is no published work on the design of new sampling plans using trigonometric-based probability distributions. In order to cover this amazing and fascinating research gap, we first introduce a novel probabilistic method called a new modified cosine-G method. A special member of the new modified cosine-G method, namely, a new modified cosine-Weibull distribution, is examined and implemented. The density function of the new model possesses symmetrical as well as asymmetrical behaviors. The usefulness and superior fitting power of the new modified cosine-Weibull distribution are demonstrated by analyzing an asymmetrical data set. Furthermore, based on the new modified cosine-Weibull distribution, we develop a new repetitive acceptance sampling strategy for attributes with specified shape parameters. Finally, a real-world application is presented to illustrate the proposed repetitive acceptance sampling strategy.
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    A New Sine-Based Distributional Method with Symmetrical and Asymmetrical Natures: Control Chart with Industrial Implication
    (MDPI AG, 2023) Alshanbari, Huda M.; Rao, Gadde Srinivasa; Seong, Jin-Taek; Khosa, Saima K.
    Control charts are widely used in quality control and industrial sectors. Because of their important role, researchers are focusing on the development of new control charts. According to our study, there is no significant amount of published work on control charts using trigonometrically generated distribution methods. In this paper, we contribute to this interesting research gap by developing a new control chart using a sine-based distributional method. The proposed distributional method (or family of probability distributions) may be called a new modified sine-G family of distributions. Based on the new modified sine-G method, a novel modification of the Weibull distribution, namely, a new modified sine-Weibull distribution, is introduced. The new modified sine-Weibull distribution is flexible enough to capture symmetrical and asymmetrical behaviors of its density function. An industrial application is considered to show the importance and implacability of the proposed distribution in quality control. Based on the proposed model, an attribute control chart is developed under a truncated life test. The control chart limits (ARLs) are also computed for the proposed model. The ARLs of the proposed control chart are compared with the attribute control chart of the Weibull distribution. The results show that the developed chart is more efficient than the existing attribute control chart for the Weibull distribution.
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    A New Sine-Based Distributional Method with Symmetrical and Asymmetrical Natures: Control Chart with Industrial Implication
    (MDPI AG, 2023) Alshanbari, Huda M.; Rao, Gadde Srinivasa; Seong, Jin-Taek; Khosa, Saima K.
    Control charts are widely used in quality control and industrial sectors. Because of their important role, researchers are focusing on the development of new control charts. According to our study, there is no significant amount of published work on control charts using trigonometrically generated distribution methods. In this paper, we contribute to this interesting research gap by developing a new control chart using a sine-based distributional method. The proposed distributional method (or family of probability distributions) may be called a new modified sine-G family of distributions. Based on the new modified sine-G method, a novel modification of the Weibull distribution, namely, a new modified sine-Weibull distribution, is introduced. The new modified sine-Weibull distribution is flexible enough to capture symmetrical and asymmetrical behaviors of its density function. An industrial application is considered to show the importance and implacability of the proposed distribution in quality control. Based on the proposed model, an attribute control chart is developed under a truncated life test. The control chart limits (ARLs) are also computed for the proposed model. The ARLs of the proposed control chart are compared with the attribute control chart of the Weibull distribution. The results show that the developed chart is more efficient than the existing attribute control chart for the Weibull distribution.
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    A new statistical methodology using the sine function: Control chart with an application to survival times data
    (Public Library of Science (PLoS), 2023) Kamal, Mustafa; Rao, Gadde Srinivasa; Alsolmi, Meshayil M.; Ahmad, Zubair; Aldallal, Ramy; Rahman, Md. Mahabubur; William Guo
    Statistical methodologies have a wider range of practical applications in every applied sector including education, reliability, management, hydrology, and healthcare sciences. Among the mentioned sectors, the implementation of statistical models in health sectors is very crucial. In the recent era, researchers have shown a deep interest in using the trigonometric function to develop new statistical methodologies. In this article, we propose a new statistical methodology using the trigonometric function, namely, a new trigonometric sine-family of distribution. A subcase (special member) of the new trigonometric sine-method called a new trigonometric sine-Weibull distribution is studied. The estimators of the new trigonometric sine-Weibull distribution are derived. A simulation study of the new trigonometric sine-Weibull distribution is also provided. The applicability of the new trigonometric sine-Weibull distribution is shown by considering a data set taken from the biomedical sector. Furthermore, we introduce an attribute control chart for the lifetime of an entity that follows the new trigonometric sine-Weibull distribution in terms of the number of failure items before a fixed time period is investigated. The performance of the suggested chart is investigated using the average run length. A comparative study and real example are given for the proposed control chart. Based on our study of the existing literature, we did not find any published work on the development of a control chart using new probability distributions that are developed based on the trigonometric function. This surprising gap is a key and interesting motivation of this research.
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    A new statistical methodology using the sine function: Control chart with an application to survival times data
    (Public Library of Science (PLoS), 2023) Kamal, Mustafa; Rao, Gadde Srinivasa; Alsolmi, Meshayil M.; Ahmad, Zubair; Aldallal, Ramy; Md. Rahman, Mahabubur; William Guo
    Statistical methodologies have a wider range of practical applications in every applied sector including education, reliability, management, hydrology, and healthcare sciences. Among the mentioned sectors, the implementation of statistical models in health sectors is very crucial. In the recent era, researchers have shown a deep interest in using the trigonometric function to develop new statistical methodologies. In this article, we propose a new statistical methodology using the trigonometric function, namely, a new trigonometric sine-G family of distribution. A subcase (special member) of the new trigonometric sine-G method called a new trigonometric sine-Weibull distribution is studied. The estimators of the new trigonometric sine-Weibull distribution are derived. A simulation study of the new trigonometric sine-Weibull distribution is also provided. The applicability of the new trigonometric sine-Weibull distribution is shown by considering a data set taken from the biomedical sector. Furthermore, we introduce an attribute control chart for the lifetime of an entity that follows the new trigonometric sine-Weibull distribution in terms of the number of failure items before a fixed time period is investigated. The performance of the suggested chart is investigated using the average run length. A comparative study and real example are given for the proposed control chart. Based on our study of the existing literature, we did not find any published work on the development of a control chart using new probability distributions that are developed based on the trigonometric function. This surprising gap is a key and interesting motivation of this research.
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    A new statistical methodology using the sine function: Control chart with an application to survival times data
    (Public Library of Science (PLoS), 2023) Kamal, Mustafa; Rao, Gadde Srinivasa; Alsolmi, Meshayil M.; Ahmad, Zubair; Aldallal, Ramy; Md. Rahman, Mahabubur; William Guo
    Statistical methodologies have a wider range of practical applications in every applied sector including education, reliability, management, hydrology, and healthcare sciences. Among the mentioned sectors, the implementation of statistical models in health sectors is very crucial. In the recent era, researchers have shown a deep interest in using the trigonometric function to develop new statistical methodologies. In this article, we propose a new statistical methodology using the trigonometric function, namely, a new trigonometric sine-G family of distribution. A subcase (special member) of the new trigonometric sine-G method called a new trigonometric sine-Weibull distribution is studied. The estimators of the new trigonometric sine-Weibull distribution are derived. A simulation study of the new trigonometric sine-Weibull distribution is also provided. The applicability of the new trigonometric sine-Weibull distribution is shown by considering a data set taken from the biomedical sector. Furthermore, we introduce an attribute control chart for the lifetime of an entity that follows the new trigonometric sine-Weibull distribution in terms of the number of failure items before a fixed time period is investigated. The performance of the suggested chart is investigated using the average run length. A comparative study and real example are given for the proposed control chart. Based on our study of the existing literature, we did not find any published work on the development of a control chart using new probability distributions that are developed based on the trigonometric function. This surprising gap is a key and interesting motivation of this research.
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    A new trigonometric modification of the Weibull distribution: Control chart and applications in quality control
    (Public Library of Science (PLoS), 2023) Alomair, Mohammed Ahmed; Ahmad, Zubair; Rao, Gadde Srinivasa; Al-Mofleh, Hazem; Khosa, Saima Khan; Al Naim, Abdulaziz Saud; Qichun Zhang
    In the most recent era, the extensions of the probability models via trigonometry methods have received great attention. This paper also offers a novel trigonometric version of the Weibull model called a type-I cosine exponentiated Weibull (for short “TICE-Weibull”) distribution. The identifiability properties for all three parameters of the TICE-Weibull model are derived. The estimators of the TICE-Weibull model are derived by implementing the maximum likelihood approach. To demonstrate the effectiveness of the TICE-Weibull model, two applications from real-world phenomena are analyzed. In addition, the proposed statistical model is established for an attribute control chart based on a time-truncated life test. The advantage of the developed charts is examined based on the average run length (ARL). The necessary tables of shift sizes and various sample sizes are offered for numerous values of the distribution parameters, as well as specified ARL and shift constants. Some numerical examples are discussed for various scheme parameters to study the performance of the new TICE-Weibull attribute control charts. According to our search and a brief study of the statistical literature, there is no published work on the development of a control chart using new probability models that are introduced using the cosine function. This is the key motivation of this work, which fills this amazing and interesting research gap.
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    A new trigonometric modification of the Weibull distribution: Control chart and applications in quality control
    (Public Library of Science (PLoS), 2023) Alomair, Mohammed Ahmed; Ahmad, Zubair; Rao, Gadde Srinivasa; Al-Mofleh, Hazem; Saima Khan Khosa; Al Naim, Abdulaziz Saud; Qichun Zhang
    In the most recent era, the extensions of the probability models via trigonometry methods have received great attention. This paper also offers a novel trigonometric version of the Weibull model called a type-I cosine exponentiated Weibull (for short “TICE-Weibull”) distribution. The identifiability properties for all three parameters of the TICE-Weibull model are derived. The estimators of the TICE-Weibull model are derived by implementing the maximum likelihood approach. To demonstrate the effectiveness of the TICE-Weibull model, two applications from real-world phenomena are analyzed. In addition, the proposed statistical model is established for an attribute control chart based on a time-truncated life test. The advantage of the developed charts is examined based on the average run length (ARL). The necessary tables of shift sizes and various sample sizes are offered for numerous values of the distribution parameters, as well as specified ARL and shift constants. Some numerical examples are discussed for various scheme parameters to study the performance of the new TICE-Weibull attribute control charts. According to our search and a brief study of the statistical literature, there is no published work on the development of a control chart using new probability models that are introduced using the cosine function. This is the key motivation of this work, which fills this amazing and interesting research gap.
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    A Weighted Cosine-G Family of Distributions: Properties and Illustration Using Time-to-Event Data
    (MDPI AG, 2023) Odhah, Omalsad Hamood; Alshanbari, Huda M.; Ahmad, Zubair; Rao, Gadde Srinivasa
    Modeling and predicting time-to-event phenomena in engineering, sports, and medical sectors are very crucial. Numerous models have been proposed for modeling such types of data sets. These models are introduced by adding one or more parameters to the traditional distributions. The addition of new parameters to the traditional distributions leads to serious issues, such as estimation consequences and re-parametrization problems. To avoid such problems, this paper introduces a new method for generating new probability distributions without any additional parameters. The proposed method may be called a weighted cosine-G family of distributions. Different distributional properties of the weighted cosine-G family, along with the maximum likelihood estimators, are obtained. A special model of the weighted cosine-G family, by utilizing the Weibull model, is considered. The special model of the weighted cosine-G family may be called a weighted cosine-Weibull distribution. A simulation study of the weighted cosine-Weibull model is conducted to evaluate the performances of its estimators. Finally, the applications of the weighted cosine-Weibull distribution are shown by considering three data sets related to the time-to-event phenomena.
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    A Weighted Cosine-G Family of Distributions: Properties and Illustration Using Time-to-Event Data
    (MDPI AG, 2023) Odhah, Omalsad Hamood; Alshanbari, Huda M.; Ahmad, Zubair; Rao, Gadde Srinivasa
    Modeling and predicting time-to-event phenomena in engineering, sports, and medical sectors are very crucial. Numerous models have been proposed for modeling such types of data sets. These models are introduced by adding one or more parameters to the traditional distributions. The addition of new parameters to the traditional distributions leads to serious issues, such as estimation consequences and re-parametrization problems. To avoid such problems, this paper introduces a new method for generating new probability distributions without any additional parameters. The proposed method may be called a weighted cosine-G family of distributions. Different distributional properties of the weighted cosine-G family, along with the maximum likelihood estimators, are obtained. A special model of the weighted cosine-G family, by utilizing the Weibull model, is considered. The special model of the weighted cosine-G family may be called a weighted cosine-Weibull distribution. A simulation study of the weighted cosine-Weibull model is conducted to evaluate the performances of its estimators. Finally, the applications of the weighted cosine-Weibull distribution are shown by considering three data sets related to the time-to-event phenomena.
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    Application of the multiple dependent state sampling strategy to late adolescent suicide rates
    (Springer Science and Business Media LLC, 2023) Kolli, Nagasaritha; Rosaiah, Kanaparthi; Rao, Gadde Srinivasa; Kirigiti, Peter Josephat
    A multiple dependent state sampling plan (MDSSP) is designed when the lifetimes of the variables follow New Lomax Rayleigh Distribution (NLRD). The decision to accept or reject a lot in the proposed methodology is based on the quality of the given present or previous lots. A binomial model-based operating characteristic curve (OC curve) for continuous lots of variables under similar settings in healthcare is used in finding the probability of acceptance, acceptance number, rejection number, and the number of preceding (succeeding) lots to consider. Time truncated life test based on the specified median of the NLRD is used in designing the current acceptance sampling plan. For specified values of the parameters of NLRD, quantile ratios, consumer’s risk and producer’s risk, average sampling number (ASN) and probability of acceptance of a lot are reported in tables. Real data on worldwide suicide rates of 15–19 years in the year 2019 from the World Health Organization (WHO) website is considered to illustrate this methodology. The minimum sample size required from the selected data to comment on worldwide suicide rates in late adolescents is explained with MDSSP. The results of the proposed acceptance sampling method are compared with the single-stage sampling plan.
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    Application of the multiple dependent state sampling strategy to late adolescent suicide rates
    (Springer Science and Business Media LLC, 2023-08-22) Kolli, Nagasaritha; Rosaiah, Kanaparthi; Rao, Gadde Srinivasa; Kirigiti, Peter Josephat
    A multiple dependent state sampling plan (MDSSP) is designed when the lifetimes of the variables follow New Lomax Rayleigh Distribution (NLRD). The decision to accept or reject a lot in the proposed methodology is based on the quality of the given present or previous lots. A binomial model-based operating characteristic curve (OC curve) for continuous lots of variables under similar settings in healthcare is used in finding the probability of acceptance, acceptance number, rejection number, and the number of preceding (succeeding) lots to consider. Time truncated life test based on the specified median of the NLRD is used in designing the current acceptance sampling plan. For specified values of the parameters of NLRD, quantile ratios, consumer’s risk and producer’s risk, average sampling number (ASN) and probability of acceptance of a lot are reported in tables. Real data on worldwide suicide rates of 15–19 years in the year 2019 from the World Health Organization (WHO) website is considered to illustrate this methodology. The minimum sample size required from the selected data to comment on worldwide suicide rates in late adolescents is explained with MDSSP. The results of the proposed acceptance sampling method are compared with the single-stage sampling plan.
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    A control chart for time truncated life tests using exponentiated half logistic distribution
    (Natural Sciences Publishing Cor., 2017) Rao, Gadde Srinivasa
    In this article, an exponentiated half logistic distribution considered to develop an attribute control chart for time truncated life tests with known or unknown shape parameter. The performance of the proposed chart is evaluated in terms of average run length (ARL) using the Monte Carlo simulation. The extensive tables are provided for the industrial use for various values of shape parameter, sample size, specified ARL and shift constants. The advantages of the proposed control chart are discussed over the existing truncated life test control charts. The performance of the proposed control chart is also studied using the simulated data sets for industrial purpose.
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    Designing of multiple dependent state repetitive sampling plan for type-II generalized half logistic distribution
    (Springer Nature, 2021) Rao, Gadde Srinivasa; Jilani, S. D.; Rao, A. Vasudeva
    In this article, we present a new multiple dependent state repetitive (MDSR) sampling plan for attributes based on consider Type-II generalized half logistic distribution (TGHLD) with known shape parameter is consider here. The optimal parameter of the proposed plan is used to determine the operating characteristic (OC) curve approach using two point’s method. The results are explained with tables. We have made the comparison of proposed design with the usual multiple dependent state (MDS) sampling plans, repetitive acceptance sampling plan (RASP) and single sampling plan (SSP) in Average Sample Number (ASN). The proposed plan is demonstrated with the help of real- life data.
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    Designing of multiple dependent state repetitive sampling plan for type-II generalized half logistic distribution
    (Springer Science and Business Media LLC, 2021) Rao, Gadde Srinivasa; Jilani, S. D.; Rao, A. Vasudeva
    In this article, we present a new multiple dependent state repetitive (MDSR) sampling plan for attributes based on consider Type-II generalized half logistic distribution (TGHLD) with known shape parameter is consider here. The optimal parameter of the proposed plan is used to determine the operating characteristic (OC) curve approach using two point’s method. The results are explained with tables. We have made the comparison of proposed design with the usual multiple dependent state (MDS) sampling plans, repetitive acceptance sampling plan (RASP) and single sampling plan (SSP) in Average Sample Number (ASN). The proposed plan is demonstrated with the help of real- life data.
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    Designing of multiple dependent state sampling plan for Type-II generalized half logistic distribution
    (Informa UK Limited, 2024) Jilani, Sd.; Rao, Gadde Srinivasa; Rao, A. Vasudeva; Yilun Shang
    In this article, we present a new multiple dependent state repetitive (MDSR) sampling plan for attributes based on consider Type-II generalized half logistic distribution (TGHLD) with known shape parameter is consider here. The optimal parameter of the proposed plan is used to determine the operating characteristic (OC) curve approach using two point’s method. The results are explained with tables. We have made the comparison of proposed design with the usual multiple dependent state (MDS) sampling plans, repetitive acceptance sampling plan (RASP) and single sampling plan (SSP) in Average Sample Number (ASN). The proposed plan is demonstrated with the help of real- life data.
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    Designing of multiple dependent state sampling plan for Type-II generalized half logistic distribution
    (Informa UK Limited, 2024-03-22) Jilani, Sd.; Rao, Gadde Srinivasa; Rao, A. Vasudeva; Yilun Shang
    In this study, we propose the multiple dependent state (MDS) sampling plan for a time truncated life test when the lifetime of product follows the Type-II Generalized Half Logistic Distribution (TGHLD). The quality of the product is considered in terms of percentile lifetime. The optimal plan parameters of the our proposed MDS sampling plan, such as the sample size, the acceptance and rejection numbers, and the number of preceding lots needed for making the decision whether to accept or reject the current lot, are determined using the approach of two points on the operating characteristic curve. Tables are obtained for various values of shape parameter and results are discussed. The real data analysis is given to illustrate the applicability of the proposed in the industry. Comparison is also made with the existing plans.
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    Estimation of reliability in multicomponent stress-strength based on dagum distribution
    (Walter de Gruyter GmbH, Berlin, 2017) Fulment, Arnold K.; Josephat, Peter K.; Rao, Gadde Srinivasa
    We consider the Dagum distribution for estimating the reliability of a k-component stress-strength system with different shape values of the shape parameter. We assume that the system has strength modelled by k independent and identically distributed random variables, and each system’s component experiences random stress. We construct maximum likelihood estimators for the system’s reliability and study their asymptotic properties. We evaluate the small sample performance of the estimators through Monte Carlo simulation. Finally, we illustrate the procedure using real data.
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    Estimation of reliability in multicomponent stress-strength based on generalized Rayleigh distribution
    (Wayne State University Library System in Detroit, 2014) Rao, Gadde Srinivasa
    A multicomponent system of k components having strengths following k- independently and identically distributed random variables x1, x2,…, xk and each component experiencing a random stress Y is considered. The system is regarded as alive only if at least s out of k (s < k) strengths exceed the stress. The reliability of such a system is obtained when strength and stress variates are given by a generalized Rayleigh distribution with different shape parameters. Reliability is estimated using the maximum likelihood (ML) method of estimation in samples drawn from strength and stress distributions; the reliability estimators are compared asymptotically. Monte-Carlo simulation is used to compare reliability estimates for the small samples and real data sets illustrate the procedure.
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    Evaluation of bootstrap confidence intervals using a new non-normal process capability index
    (Multidisciplinary Digital Publishing Institute, 2019) Rao, Gadde Srinivasa; Albassam, Mohammed; Aslam, Muhammad
    This paper assesses the bootstrap confidence intervals of a newly proposed process capability index (PCI) forWeibull distribution, using the logarithm of the analyzed data. These methods can be applied when the quality of interest has non-symmetrical distribution. Bootstrap confidence intervals, which consist of standard bootstrap (SB), percentile bootstrap (PB), and bias-corrected percentile bootstrap (BCPB) confidence interval are constructed for the proposed method. A Monte Carlo simulation study is used to determine the efficiency of newly proposed index Cpkw over the existing method by addressing the coverage probabilities and average widths. The outcome shows that the BCPB confidence interval is recommended. The methodology of the proposed index has been explained by using the real data of breaking stress of carbon fibers.