i-manager Publications

i-manager's Journal on Mathematics (JMAT)

Current Issue Vol. 13 Issue 2

Mathematical Modeling of Higher Overtone Vibrational Frequencies in Dichlorine Monoxide
Some Types of Generalized Closed and Generalized Star Closed Sets in Topological Ordered Spaces
Optimizing Capsule Endoscopy Detection: A Deep Learning Approach with L-Softmax and Laplacian-SGD
Kernel Ideals in Semigroups
Modeling the Dynamics of Covid-19 with the Inclusion of Treatment, Vaccination and Natural Cure
Calculation of Combined Vibrational Frequencies in Cl₂O using Lie Algebraic Method

Most Cited

Volume 5 Issue 4 October - December 2016

Research Paper

Common Coupled Fixed Point Theorems in Fuzzy Metric Spaces

RAKESH* , P Srikanth Rao**

* Associate Professor, Department of Mathematics, Aurora’s Technological Institute, Hyderabad, Telangana, India.

** Professor, Department of Mathematics, B. V. Raju Institute of Technology, Narsapur, Telangana, India.

Singh, T.R., and Rao, P.S. (2016). Common Coupled Fixed Point Theorems in Fuzzy Metric Spaces. i-manager’s Journal on Mathematics, 5(4), 1-10. https://doi.org/10.26634/jmat.5.4.8305

Abstract

A fuzzy set of X is a function with domain X and values in [0, 1]. If A is a fuzzy set and x ? X, then the function values A(x) are called the grade of membership of x in A. A mapping F from X to F(Y) is called a fuzzy mapping if for each x ? X; F(x) is a fuzzy set on Y and F(x)(y) denotes the degree of membership of y in F(x). Let X be a metric linear space and let W(X) denote the set of all fuzzy sets on X such that each of its α-cut is a nonempty compact and convex subset (approximate quantity) of X. A fuzzy mapping F from X to W(X) is called a fuzzy contraction mapping if there exists q ? (0, 1) such that D(F(x), F(y)) ≤ qd(x, y) for each x,y ? X. In this paper, two common coupled fixed point theorems for six self maps is proved under Wcompatible conditions in fuzzy metric spaces. Coupled fixed point and coupled point of coincidence for contractive mappings in complete fuzzy metric space is also obtained. The results obtain an extension of Theorem 2.1 by K. Pandu Ranga Rao, K. Rama Koteswara Rao, and S. Sedghi, (2014) [11]. Common Coupled Fixed Point Theorems in Fuzzy Metric Spaces. Finally, an example has been given to illustrate the usability of the main result.

References

[1]. A. George and P. Veeramani, (1994). “On some result in fuzzy metric space”. Fuzzy Sets Syst., Vol.64, pp.395-399.

[2]. B. Schweizer and A. Sklar, (1960). “Statistical metric spaces”. Pacific J. Math., Vol.10, pp.313-334.

[3]. B. Singh and M. S. Chauhan, (2000). “Common fixed points of compatible maps in fuzzy metric spaces”. Fuzzy Sets Syst., Vol.115, No.3, pp.471-475.

[4]. B. Singh and S. Jain, (2005). “Semi-compatibility and fixed point theorems in fuzzy metric space using implicit relation”. Internat. J. Math. Math. Sci., Vol.16, pp.2617-2629.

[5]. B.Singh and S. Jain, (2005). “Semi-compatibility, compatibility and fixed point theorems in fuzzy metric space”. J.Chung Cheong Math. Soc., Vol.18, No.1, pp.1-22.

[6]. C. Alaca, (2010). “Fixed point results for mappings satisfying a general contractive condition of operator type in dislocated fuzzy quasi-metric spaces”. J. Comput.Anal. Appl., Vol.12, No.1-b, pp.361-368.

[7]. C. Alaca, D. Turkoglu and C. Yildiz, (2006). “Fixed Points in Intuitionistic Fuzzy Metric Spaces”. Chaos, Solitons & Fractals, Vol.29, No.5, pp.1073-1078.

[8]. D. Turkoglu, C. Alaca, Y. J. Cho, and C. Yildiz, (2006). “Common Fixed Point Theorems in Intuitionistic Fuzzy Metric Spaces”. J. Appl. Math. Comput., Vol.22, No.1-2, pp.411-424.

[9]. D. Turkoglu, I. Altun, and B. Fisher, (2006). “Common fixed point theorems for four mappings with some weak conditions of commutativity”. Novi. Sad. J. Math., Vol.36, No.1, pp.75-86.

[10]. I. Altun and D. Turkoglu, “Fixed points of sequences of maps on fuzzy metric spaces”. Ital. J. Pure Appl.Math, Vol.24.

[11]. K. Pandu Ranga Rao, K. Rama Koteswara Rao, and S. Sedghi, (2014). “Common Coupled Fixed Point Theorems in Fuzzy Metric Spaces”. GU. J. Sci, Vol.27, No.2, pp.739-745.

[12]. J. Rodríguez López, and S. Ramaguera, (2004). “The Hausdorff fuzzy metric on compact sets”. Fuzzy Sets Sys, Vol.147.

[13]. L. A. Zadeh, (1965). “Fuzzy sets”. Inform and Control, Vol.8, pp.338-353.

[14]. M. Abbas, M. Alikhan, and S. Radenovic, (2010). “Common coupled fixed point theorems in cone metric spaces for W-compatible Mappings”. Applied Mathematics and Computation, Vol.217, No.1, pp.195-202.

[15]. M. Grabiec, (1988). “Fixed points in fuzzy metric spaces”. Fuzzy Sets Syst., Vol.27, pp.385-389.

[16]. O. Hadzic and E. Pap, (2002). “A fixed point theorem for multi valued mappings in probabilistic metric spaces and an application in fuzzy metric spaces”. Fuzzy Sets Syst., Vol.127, pp.333-344.

[17]. R. Chugh and S. Kumar, (2002). “Common fixed point theorems in fuzzy metric spaces”. Bull. Cal. Math. Soc., Vol.94, No.1.

[18]. R. Saadati, A. Razani, and H. Adibi, (2006). “A common fixed point theorem in -fuzzy metric spaces”. Chaos, Solitons and Fractals, Chaos, pp.01-023.

[19]. R. Vasuki, (1999). “Common fixed points for R-weakly commuting maps in fuzzy metric spaces”. Indian J. Pure Appl. Math., Vol.30, pp.419-423.

[20]. S. N. Mishra, S. N. Sharma, and S. L. Singh, (1994). “Common fixed points of maps in fuzzy metric spaces”. Internat. J. Math. Math. Sci., Vol.17, pp.253-258.

[21]. S. Sharma, (2002). “Common fixed point theorems in fuzzy metric spaces”. Fuzzy Sets Syst., Vol.127, pp.345-352.

[22]. Shaban Sedghi, Ishak Altun, and Nabi Shobe, (2010). “Coupled fixed point theorems for contractions in fuzzy metric spaces”. Nonlinear Analysis, Vol.72, pp.1298-1304.

[23]. T.G. Bhaskar, and V. Lakshmikantham, (2006). “Fixed point theorems in partially ordered cone metric spaces and applications, Nonlinear Analysis”. Theory, Methods and Applications, Vol.65, No.7, pp.825-832.

[24]. Xin-Qi Hu, (2011). “Common coupled fixed point theorems for contractive mappings in fuzzy metric spaces”. Fixed Point Theory and Applications, Article ID 363716, 14 pages, doi: 10.1155/2011/363716.

[25]. Y.J. Cho, (1997). “Fixed points in fuzzy metric spaces”. J. Fuzzy Math., Vol.5, pp.949-962.

[26]. Y. J. Cho, H. K. Pathak, S. M. Kang and J. S. Jung, (1998). “Common fixed points of compatible maps of type (ß ) on fuzzy metric spaces”. Fuzzy Sets Syst. Vol.93, pp.99-111.

Full Article (HTML)

Pdf

Research Paper

Modified Maximum Likelihood Estimation: Inverse Half Logistic Distribution

R. Subba Rao* , Pushpa Latha Mamidi, R. R. L. Kantam*

* Professor, Department of Mathematics, SRKR Engineering College, Bhimavaram, Andhra Pradesh, India.

Assistant Professor, Department of Mathematics, Vishnu Institute of Technology, Bhimavaram, Andhra Pradesh, India.

* Retired Professor, Department of Statistics, Acharya Nagarjuna University, Nagarjuna Nagar, Guntur, Andhra Pradesh, India.

Rao, R.S., Mamidi, P.L., and Kantam, R.R.L. (2016). Modified Maximum Likelihood Estimation: Inverse Half Logistic Distribution. i-manager’s Journal on Mathematics, 5(4), 11-19. https://doi.org/10.26634/jmat.5.4.8306

Abstract

If a random variable follows a particular distribution, then the distribution of the inverse of that random variable is called inverted distribution. In this paper, the pdf of Inverse Half Logistic Distribution (IHLD) is derived. The mathematical properties of this distribution have been studied. The parameter is estimated from a complete sample using the classical maximum likelihood method. The estimating equations are modified to get simpler and efficient estimators. Two methods of modification are suggested. The sampling characteristics of the modified estimates are also presented for performance comparisons.

References

[1]. Tiku, M.L., (1967). “Estimating the Mean and Standard deviation from a Censored Normal Sample”. Biometrica, Vol.54, pp.155-165.

[2]. Mehrotra, K.G., and Nanda, P., (1974). “Unbiased Estimation of Parameters by Order Statistics in the case of Censored samples”. Biometrika, Vol.61, pp.601-606.

[3]. Pearson, E.S., and Rootzen, H. (1977). “Simple and Highly Efficient Estimators for a Type-I Censored Normal Sample”. Biometrika, Vol.64, No.1, pp.123-128.

[4]. Rosaiah, K., Kantam, R.R.L., and Narasimham, V.L., (1993). “ML and Modified ML Estimation in Gamma Distribution with a known Prior Relation among the parameters”. Pakistan Journal of Statistics, Vol.9, No.3B, pp.37-48.

[5]. Kantam, R.R.L., and Sriram, B., (2001). “Variable control charts based on Gamma distribution”. IAPQR Transactions, Vol.26, No.2, pp.63-77.

[6]. Kantam, R.R.L., and Srinivasa Rao, G. (2002). “Log-Logistic Distribution: Modified Maximum Likelihood Estimation”. Gujarat Statistical Review, Vol.29, No.1 & 2, pp.25-36.

[7]. Kantam and Sriram, (2003). “Maximum Likelihood Estimation from Censored Samples – Some Modifications in Length Biased version of Exponential Model”. Statistical Methods, Vol.5, No.1, pp.63-78.

[8]. K. Rosaiah, and R.R.L. Kantam, (2005). “Acceptance Sampling based on the Inverse Rayleigh Distribution”. Economic Quality Control, Vol.20, No.2, pp.277-286.

[9]. Kersey, and Jing Xiong, (2010). Weighted Inverse Weibull and Beta-Inverse Weibull Distribution (Doctoral Dissertations). Retrieved from Digital Commons - Georgia Southern, 661.

[10]. R. Subba Rao, and R.R.L. Kantam, (2010). “Pareto Distribution- some methods of Estimation”. International Journal of Computational Mathematical Ideas, Vol.2, No.1 & 2.

[11]. Gyan Prakash, (2011). “Bayes Shrinkage Minimax Estimation in Inverse Gaussian distribution”. Applied Mathematics, No.2, pp.830-835.

[12]. B. Srinivasa Rao, J. Pratapa Reddy, and K. Rosaiah, (2012a). “Extreme value charts and ANOM based on Inverse Rayleigh Distribution”. Pakistan Journal of Statistics and Operation Research, Vol.8, No.4, pp.759-766 .

[13]. G. Srinivasa Rao, R.R.L. Kantam, K. Rosaiah, and J. Pratapa Reddy, (2012b). “Acceptance Sampling Plans for percentiles based on the Inverse Rayleigh Distribution”. Electron. J. App. Stat. Anal., Vol.5, No.2, pp.164-177.

[14]. Muhammad Qaiser Shahbaz, Saman Shahbaz, and Nadeem Shafique Butt, (2012). “The Kumaraswamy-Invere Weibull Distribution”. Pak. J. Stat. Oper. Res. Vol.8, No.3, pp.479-489.

[15]. B.Vara Prasad Rao, K.Gangadhara Rao, and B. Srinivasa Rao, (2013). “Inverse Rayleigh Software Reliability Growth Model”. International Journal of Computer Applications, Vol.75, No.6, pp.0975-8887.

[16]. B.Srinivasa Rao, R.R.L.Kantam, and J. Pratapa Reddy, (2013). “Variable Control Charts based on Inverse Rayleigh Distribution”. Journal of Applied Probability and Statistics, Vol.8, No.1, pp.46-57.

[17]. Farhad Yahgmaei, Manoochehr Babanezhad, and Omid S. Moghadam, (2013). “Bayesian Estimation of the Scale Parameter of Inverse Weibull Distribution under the Asymmetric Loss Functions”. Journal of Probability and Statistics, Vol.2013.

[18]. Jeremias Leao, Helton Saulo, Marcelo Bourguignon, Rematp Cintra, Leandro Rego, and Gauss Cordeiro, (2013). “On some properties of the Beta Inverse Rayleigh Distribution”. Chilean Journal of Statistics, Vol.4, No.2, pp.111-131.

[19]. Kantam, R.R.L., Priya, Ch., M., and Ravi Kumar, M.S., (2013). “Modified Maximum Likelihood Estimation in Linear Failure Rate Distribuiton”. InterStat: Statistics on the Internet, Vol.7, No.6.

[20]. Kanchan Jain, Neetu Singla, and Suresh Kumar Sharma, (2014). “The Generalized Inverse Generalized Weibull Distribution and Its Properties”. Journal of Probability, Vol.2014.

[21]. Kusum Lata Singh and R.S. Srivastava, (2014). “Inverse Maxwell Distribution as a Survival Model, Genesis and Parameter Estimation”. Research Journal of Mathematical and Statistical Sciences, Vol.2, No.7, pp.23-28.

[22]. Muhammad Shuaib Khan, (2014). “Modified Inverse Rayleigh Distribution”. International Journal of Computer Applications, Vol. 87, No.13, pp.0975-8887.

[23]. Pawan Kumar Srivastava, and R.S. Srivastava, (2014). “Two Parameter Inverse Chen Distribution as Survival Model”. International Journal of Statistika and Mathematika, Vol.11.

[24]. Reza Azimi and Faramarz Azimi Sarikhanbaglu, (2014). “Bayesian Estimation for the Kumaraswamy-inverse Rayleigh distributon based on progressive first failure censored samples”. International Journal of Scientific World, Vol.2, No.2, pp.42- 47.

[25]. Elbatal, Hiba Z, and Muhammed, (2014). “Exponentiated Generalised Inverse Weibull distribution”. Applied Mathematical Sciences, Vol.8, No.81, pp.3997-4012.

[26]. Ibrahim Elbatal, Francesca Condino, and Filippo Domma, (2014). “Reflected Generalized Beta Inverse Weibull Distribution: definition and properties”. arXiv: 1309.6108 [math.ST].

[27]. R. Subba Rao, R.R.L. Kantam, and G. Prasad, (2015). “Modified Maximum likelihood Estimation in Pareto-Rayleigh distribution”. Golden Research Thoughts, pp.140-152.

[28]. Taras Bodnar, Stepan Mazur, and Krzysztof Podgorski, (2015). “Singular Inverse Wishart Distribution with Application to Portfolio Theory”. Mathematical Statistics Stockholm University Research Report 8.

Full Article (HTML)

Pdf

Research Paper

Some coupled fixed point theorems in M- fuzzy metric spaces using the common (E.A) property

Dr Pranjali* , Shailesh Dhar Diwan**

* Senior Assistant Professor, Department of Mathematics, Shri Shankaracharya Institute of Prof. Mgmt. and Tech., Raipur (C.G.), India.

** Associate Professor, Department of Mathematics, Government Engineering College, Raipur (C.G.), India.

Sharma, P., and Diwan, S.D. (2016). Some Coupled Fixed Point Theorems in M-Fuzzy Metric Spaces using the Common (E.A.) Property. i-manager’s Journal on Mathematics, 5(4), 20-29. https://doi.org/10.26634/jmat.5.4.8307

Abstract

In this paper, the authors have defined some properties in M-fuzzy metric spaces defined by Sedgi and Shobe [15] and they established some common coupled fixed point theorems in M-fuzzy metric space using an implicit relation. They defined the notion of (E.A.) property and common (E.A.) property for the pair of mappings defined in — fuzzy metric space. The obtained results extend, generalize, and improve several results of D - metric spaces defined by Dhage [3] and metric spaces to generalized fuzzy metric spaces or M-fuzzy metric spaces.

References

[1] Aamri M. and Moutawakil D. E., (2002). “Some new common fixed point theorems under strict contractive conditions”. Journal of Mathematical Analysis and Applications, Vol.270, No.1, pp.181-188.

[2]. Ali J., Imdad M., and Bahuguna D., (2010). “Common fixed point theorems in Menger spaces with common property (E.A.)”. Comput. Math. Appl., Vol.60, No.12, pp.3152-3159.

[3]. Dhage B. C., (1992). “Generalised metric spaces and mappings with fixed point”. Bull. Calcutt Math Soc., Vol.84, No.4, pp.329- 336.

[4]. George A., and Veeramani P., (1994). “On some results in Fuzzy Metric Spaces”. Fuzzy Sets and System, Vol.64, pp.395- 399.

[5]. Grabiec M., (1989). “Fixed points in fuzzy metric spaces”. Fuzzy Sets and Systems, Vol.27, pp.385-389.

[6]. Gregori V. and Sapena A., (2002). “On Fixed Point Theorem in Fuzzy Metric Spaces”. Fuzzy Sets and Systems, Vol.125, pp.245-252.

[7]. Jungck, G., (1976). “Commuting mappings and fixed points”. Amer. Math. Monthly, Vol.83, pp.261-263.

[8]. Jungck G., (1986). “Compatible mappings and common fixed points”. Internet. J. Math. Math. Sci., Vol.9, pp.771-779.

[9]. Jungck G. and Rhoades B.E., (2006). “Fixed point Theorems for occasionally weakly compatible mappings”. Fixed Point Theory, Vol.7, pp.286-296.

[10]. Kramosil O. and Michalek J., (1975). “Fuzzy Metric and statistical metric spaces”. Kybernetika, Vol.11, pp.326-334.

[11]. Mihet D., (2010). “Fixed point theorems in fuzzy metric spaces using property (E.A.)”. Nonlinear Anal. Vol.73, pp.2184- 2188.

[12]. Mishra S.N., (1991). “Common fixed points of compatible mappings in PM spaces”. Math. Japon., Vol.36, pp.283-289.

[13]. Pant R.P., (1994). “Common fixed points of non commuting mappings”. J. Math. Anal. Appl., Vol.188, No.2, pp.436-440.

[14]. Schweizer B. and Sclar A., (1960). “Statistical Metric space”. Pacific J. Math., pp.314-334.

[15]. Sedghi S. and Shobe N., (2007). “A common fixed point theorem in two m-fuzzy metric spaces”. Commun. Korean Math. Soc., Vol.22, No.4, pp.513-526.

[16]. Sessa S., (1986). “On a weak commutativity condition in a fixed point considation”. Publication of Inst. Mathematics, Vol.32, No.46, pp.149-153.

[17]. Vasuki R., (1999). “Common fixed points for R-weakly commuting maps in fuzzy metric spaces”. Indian J. Pure Appl. Math. Vol.30, pp.419-423.

[18]. Zadeh L.A., (1965). “Fuzzy sets”. Inform and Control, Vol.8, pp.338-353.

Full Article (HTML)

Pdf

Research Paper

Advanced Tri–Analytic Trichotomous Post Hoc Repeated Measures forTri–Squared Test Inventive Investigative Instrument Items Using Trichotomous Variation Analysis [Trivariant Analysis]

James Edward Osler II*

Associate Professor, Department of Curriculum and Instruction, North Carolina Central University, USA.

Osler, J. E., II. (2016). Advanced Tri–Analytic Trichotomous Post Hoc Repeated Measures for Tri–Squared Test Inventive Investigative Instrument items using Trichotomous Variation Analysis [Trivariant Analysis]. i-manager’s Journal on Mathematics, 5(4), 30-46. https://doi.org/10.26634/jmat.5.4.8308

Abstract

This monograph provides an epistemological rational for the Post Hoc testing of the transformative process of qualitative data into quantitative outcomes through the Tri–Squared Test introduced in the Journal on Mathematics, and further detailed in the Journal on Educational Technology, Journal on School Educational Technology, and in Journal on Educational Psychology articles. Advanced statistical measures of internal research instrument Trichotomous Repeated Measures and Trichotomous Variation of significant Transformative Trichotomy–Squared [Tri–Squared] research variables are analyzed. This additional novel approach to advanced Tri–Squared data analysis adds additional value to the mixed methods approach of research design that involves the holistic combination and comparison of qualitative and quantitative data outcomes. Multiple sequential mathematical models are provided that illustrate the entire process of advanced Tri–Analytic inquiry.

References

[1]. Osler, J. E. (2012a). “Trichotomy–Squared – A novel mixed methods test and research procedure designed to analyze, transform, and compare qualitative and quantitative data for education scientists who are administrators, practitioners, teachers, and technologists”. i-manager’s Journal on Mathematics, Vol.1, No.3, pp.23-31.

[2]. Osler, J. E. & Waden, C. (2012b). “Using Innovative Technical Solutions as an Intervention for At Risk Students: A Meta–Cognitive Statistical Analysis to Determine the Impact of Ninth Grade Freshman Academies, Centers, and Center Models Upon Minority Student Retention and Achievement”. i-manager’s Journal on School Educational Technology, Vol.7, No.3, pp.11-23.

[3]. Osler, J. E. (2013). “The Psychological Efficacy of Education as a Science through Personal, Professional, and Contextual Inquiry of the Affective Learning Domain”. i-manager’s Journal on Educational Psychology, Vol.6, No.4, pp.36-41.

[4]. Osler, J. E. (2014a). “Triostatistics: The Application of Innovative In–Depth Advanced Post Hoc Statistical Metrics for the Assessment and Analysis of Statistically Significant Tri–Squared Test Outcomes”. Kentucky Journal of Excellence in College Teaching and Learning, Vol.12, No.3, pp.27-39.

[5]. Osler, J. E. (2014b). “Introducing TRINOVA: Trichotomous Nomographical Variance - A Post Hoc Advanced Statistical Test of Between and Within Group Variances of Trichotomous Categorical and Outcome Variables of a Significant Tri–Squared Test”. i-manager's Journal on Mathematics, Vol.3, No.4, pp.1-14.

[6]. Osler, J. E. & Mason, L. R. (2015). “Neuromathematical Trichotomous Mixed Methods Analysis: Using the Neuroscientific Tri–Squared Test Statistical Metric as a Post Hoc Analytic to Determine North Carolina School of Science and Mathematics Leadership Efficacy”. i-manager's Journal on Educational Psychology, Vol.9, No.3, pp.42-59.

[7]. Rust, J. & Golombok, S. (1989). Modern Psychometrics: The Science of Psychological Assessment (2 ed.). Florence, KY, US: Taylor & Frances/Routledge.

[8]. Searle, S. R., & Casella, G. Mcculloch. CE (1992). Variance Components. John Wiley & Sons, Inc.

Full Article (HTML)

Pdf

Research Paper

Extreme Value Control Chart for Burr Type XII Distribution

M.S. Ravi Kumar* , R. R. L. Kantam**

* Associate Professor, Department of Community Medicine, Konaseema Institute of Medical Sciences & Research Foundation, Amalapuram, Andhra Pradesh, India.

** Retired Professor, Department of Statistics, Acharya Nagarjuna University, Nagarjunanagar, Andhra Pradesh, India.

Ravikumar, M.S., and Kantam, R.R.L. (2016). Extreme Value Control Chart for Burr Type XII Distribution. i-manager’s Journal on Mathematics, 5(4), 47-51. https://doi.org/10.26634/jmat.5.4.8309

Abstract

Variable control charts are based on subgroup statistics and variation in the values of the subgroup statistics between subgroups. In this paper, sampling distribution of extreme order statistics for a given sample from Burr Type XII Distribution are considered and its percentiles are used to develop an extreme value control chart for a process variate. The approximation to Normal Distribution of the Burr Distribution is explored to develop the technique of popular ANalysis Of Means (ANOM) through Burr Distribution. Comparative study of the approximations are made. The results are explained by an illustration.

References

[1]. John A. Austin, Jr. (1973). “Control Chart Constants for Largest and Smallest in Sampling from a Normal Distribution using the Generalized Burr Distribution”. Technometrics, Vol.15, No.4, pp.931-933.

[2]. Kantam, R.R.L and Ravikumar, M.S. (2013). “Variable Control Charts in Inverse Gaussian Distribution”. Proceedings of National Conference on Mathematical Sciences and Applications, pp.161-164.

[3]. Kantam, R.R.L and Ravikumar, M.S. (2013). “Time Control Chart – Some IFR Models”. InterStat, pp.1-10.

[4]. Kantam, R.R.L and Ravikumar, M.S. (2013). “Time Control Chart - Burr Distribution”. Collection of Recent Statistical Methods and Applications, A Publication of Department of Statistics, University of Kerala, pp.307-314.

[5]. Kantam, R.R.L., SriRam, B., and Srinivas, V. (2013). “Extreme Value Control Charts in Some Life Testing Models”. International Journal of Scientific and Research Publications, Vol.3, No.9, pp.1-4.

[6]. Montgomery Douglas C. (2001). Introduction to Statistical Quality Control. Third Edition, WSE, pp.213.

[7]. Raid W. Amin and Hans W. Wolff. (2007). “The Behavior of an Extreme - Value Control Charts in the Case of Mixture Alternatives”. The Case of Mixture Alternatives, Sequential Analysis-Design Methods and Applications, Published online (Taylor & Francis Online), pp.35-51.

[8]. Rungsarit Intaramo, and Adisak Pongpullponsak, (2012). “Development of Fuzzy Extreme Value Theory Control Charts Using a -cuts for Skewed Populations”. Applied Mathematical Sciences, Vol.6, No.117, pp.5811-5834.

[9]. Srinivasa Rao, B., Pratapa Reddy, J., and Sarath Babu, G. (2012). “Extreme Value Charts and Analysis of Means (ANOM) Based on the Log Logistic Distribution”. Journal of Modern Applied Statistical Methods, Vol.11, No.2, pp.493-505.

[10]. Srinivasa Rao B. and Kantam, R.R.L. (2012). “Extreme value charts and analysis of means based on half logistic distribution”. International Journal of Quality & Reliability Management, Vol.29, No.5, pp.501-511.

i-manager's Journal on Mathematics (JMAT)

Current Issue Vol. 13 Issue 2

Most Read

Most Cited

Volume 5 Issue 4 October - December 2016

Common Coupled Fixed Point Theorems in Fuzzy Metric Spaces

RAKESH* , P Srikanth Rao**

* Associate Professor, Department of Mathematics, Aurora’s Technological Institute, Hyderabad, Telangana, India. ** Professor, Department of Mathematics, B. V. Raju Institute of Technology, Narsapur, Telangana, India.

Singh, T.R., and Rao, P.S. (2016). Common Coupled Fixed Point Theorems in Fuzzy Metric Spaces. i-manager’s Journal on Mathematics, 5(4), 1-10. https://doi.org/10.26634/jmat.5.4.8305

Abstract

References

Full Article (HTML)

Pdf

Modified Maximum Likelihood Estimation: Inverse Half Logistic Distribution

R. Subba Rao* , Pushpa Latha Mamidi**, R. R. L. Kantam***

Rao, R.S., Mamidi, P.L., and Kantam, R.R.L. (2016). Modified Maximum Likelihood Estimation: Inverse Half Logistic Distribution. i-manager’s Journal on Mathematics, 5(4), 11-19. https://doi.org/10.26634/jmat.5.4.8306

Abstract

References

Full Article (HTML)

Pdf

Some coupled fixed point theorems in M- fuzzy metric spaces using the common (E.A) property

Dr Pranjali* , Shailesh Dhar Diwan**

* Senior Assistant Professor, Department of Mathematics, Shri Shankaracharya Institute of Prof. Mgmt. and Tech., Raipur (C.G.), India. ** Associate Professor, Department of Mathematics, Government Engineering College, Raipur (C.G.), India.

Sharma, P., and Diwan, S.D. (2016). Some Coupled Fixed Point Theorems in M-Fuzzy Metric Spaces using the Common (E.A.) Property. i-manager’s Journal on Mathematics, 5(4), 20-29. https://doi.org/10.26634/jmat.5.4.8307

Abstract

References

Full Article (HTML)

Pdf

Advanced Tri–Analytic Trichotomous Post Hoc Repeated Measures forTri–Squared Test Inventive Investigative Instrument Items Using Trichotomous Variation Analysis [Trivariant Analysis]

James Edward Osler II*

Associate Professor, Department of Curriculum and Instruction, North Carolina Central University, USA.

Abstract

References

Full Article (HTML)

Pdf

Extreme Value Control Chart for Burr Type XII Distribution

M.S. Ravi Kumar* , R. R. L. Kantam**

* Associate Professor, Department of Community Medicine, Konaseema Institute of Medical Sciences & Research Foundation, Amalapuram, Andhra Pradesh, India. ** Retired Professor, Department of Statistics, Acharya Nagarjuna University, Nagarjunanagar, Andhra Pradesh, India.

Ravikumar, M.S., and Kantam, R.R.L. (2016). Extreme Value Control Chart for Burr Type XII Distribution. i-manager’s Journal on Mathematics, 5(4), 47-51. https://doi.org/10.26634/jmat.5.4.8309

Abstract

References

Full Article (HTML)

Pdf

* Associate Professor, Department of Mathematics, Aurora’s Technological Institute, Hyderabad, Telangana, India.

** Professor, Department of Mathematics, B. V. Raju Institute of Technology, Narsapur, Telangana, India.

R. Subba Rao* , Pushpa Latha Mamidi, R. R. L. Kantam*

* Senior Assistant Professor, Department of Mathematics, Shri Shankaracharya Institute of Prof. Mgmt. and Tech., Raipur (C.G.), India.

** Associate Professor, Department of Mathematics, Government Engineering College, Raipur (C.G.), India.

* Associate Professor, Department of Community Medicine, Konaseema Institute of Medical Sciences & Research Foundation, Amalapuram, Andhra Pradesh, India.

** Retired Professor, Department of Statistics, Acharya Nagarjuna University, Nagarjunanagar, Andhra Pradesh, India.