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Journal Cover   Research & Reviews : Journal of Statistics
   Full-text available via subscription Subscription journal
   ISSN (Print) 2348-7909 - ISSN (Online) 2278-2273
   Published by STM Journals Homepage  [61 journals]
  • Hybrid Bernoulli-Triangular Distribution
    • Authors: B. Ramya, S. Sampath
      Abstract: Chance theory deals with environments where both randomness and fuzziness coexist. This paper considers the development of a new hybrid distribution called “Bernouli-Triangular” distribution which treats the parameter involved in classical Bernouli distribution as a triangular fuzzy variable. Theoretical expressions for Chance distribution, its mean and variance are derived for various cases arising in the hybrid distribution developed in this work. It was noticed that the expressions for mean and variance of the hybrid Bernouli-Triangular distribution resemble those corresponding to Bernouli probability distribution.Keywords: Chance measure, hybrid variable, hybrid Bernouli-Triangular distribution, chance distribution, expected value, varianceCite this Article: Ramya B, Sampath S, Hybrid Bernoulli-Triangular Distribution. Research & Reviews: Journal of Statistics. 2015; 4(1): 8–19p.
      PubDate: 2015-04-27
      Issue No: Vol. 4 (2015)
  • On Estimation of R=P for Birnbaum-Saunders Distribution
    • Authors: Shayla Naznin, Md. Soyebur Rahman
      Abstract: On Estimation of R=P(Y<X) for Birnbaum-Saunders DistributionIn this paper the estimation of R=P(Y<X) is performed. Where Y and X are two independent Birnbaum-Saunders distribution, when Y is stress and X is strength. Monte-Carlo simulation is performed to obtain the estimate of R. The MLE of the R is obtained from iterative method.Keywords- Stress-Strength model, maximum likelihood estimator, stress, strength, reliabilityCite this Article: Shayla Naznin, Md. Soyebur Rahman. On Estimation of R=P(Y<X) for Birnbaum-Saunders Distribution. Research & Reviews: Journal of Statistics. 2015; 4(1): 1–7p.
      PubDate: 2015-04-27
      Issue No: Vol. 4 (2015)
  • Probabilistic Approach to Explore Indian Population Trends
    • Authors: Kumari Shivangi, Harinarayan Tiwari, Randhir Kumar Chaudhary
      Abstract: This paper presents a stochastic description of the total population (census data) of India. An estimate to their distribution can be obtained using three non-linear distributions; Beta, Johnson SB & Power Function. Total population of India have a quadratic polynomial trend and best fitted with Johnson SB distribution. Beta and power function distribution both under predict the maximum value and over predict the minimum value. Johnson SB distribution over predicts the maximum value and under predicts the minimum value so it can nearby range of population that lies between the distributions. It also provides new approach to think for population forecasting.Keywords: India, population, probability, beta distribution, census, power functionCite this Article: Kumari Shivangi, Harinarayan Tiwari, Randhir Kumar Chaudhary. Probabilistic approach to explore Indian population trends. Research & Reviews: Journal of Statistics. 2015; 4(1): 20–25p.
      PubDate: 2015-04-27
      Issue No: Vol. 4 (2015)
  • Bayesian Modified Chain Sampling Plan
    • Authors: H. Akamanchi Raghottam, J. Jothikumar
      Abstract: Chain sampling plan (ChSP-1) is a sampling plan applicable in situations involving small samples and costly or destructive testing and replaces zero acceptance number single sampling plans. The current lot is accepted under ChSP-1 if the samples from the previous consecutive lots do not have nonconforming products and the sample from the current lot has one or no nonconforming product. Though the operating characteristic curve of ChSP-1 discriminates the lots of good and poor quality lot well, the plan does not help to reduce the sample size. The modified chain sampling plan (MChSP-1) was proposed with a modification in chaining the results of the previous consecutive results in order to obtain plan with smaller sample size than ChSP-1. This paper discusses the MChSP-1 in the Bayesian approach, employing gamma prior distribution to the parameter in the Poisson distribution. The operating characteristic function, a measure of performance of sampling plans, of the Bayesian modified chain sampling plan is derived. Properties of the operating characteristic function are studied using empirical results.Keywords: Operating characteristic (OC) function, probability of acceptance(pa), modified chain sampling plan (MChSP-1), Bayesian modified chain sampling plan (BMChSP-1)
      PubDate: 2015-01-05
      Issue No: Vol. 3 (2015)
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