Best Fit Probability Distribution Analysis of Major Crop Paddy of Rice Bowl State of India-Telangana

L. Rajani Devi and V. V. HaraGopal
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L. Rajani Devi: Telangana Mahila Viswavidyalayam (UCW, Koti), India
V. V. HaraGopal: Osmania University Hyderabad BITS Pilani, India

European Journal of Mathematics and Statistics, 2023, vol. 4, issue 2, 10-18

Abstract: Telangana state's population is mostly dependent on agriculture. The Telangana state's economy depends heavily on agriculture, as does the nation's and the state's ability to achieve food security. Combining art and science to fit a statistical distribution to data involves making trade-offs along the way. The secret to effective data analysis is striking a balance between improving distributional fit and preserving ease of estimation while keeping in mind that the analysis's ultimate goal is to help you make better decisions. A recurring issue in agricultural research was which distribution should be utilized to simulate the production data from an experiment. An analysis is then carried out utilizing the obtained distributions using the statistical method to fit probability distributions to data of variables. These distributions would be a representation of the properties of the variable data. The twenty distributions are: Cauchy, Error, Hypersequent, Gamma(3p), Laplace, Logistic, Log Pearson 3, Rayleigh (2p), Weibull (3p), Log Logistic (3p), Triangular, Gen Gamma, Gen.Gamma(4p), Gen.Extreme Value, Log Normal (3p), Pearson 5 (3p), Fatigue life (3p), Inv. Gaussian (3p), Nakagami, In order to suit a distribution research, rice distributions are used. Twenty probability distributions were computed, and the test statistic Kolmogorov-Smirnov test, Anderson-Darling test, Chi-Square test, and each data set were used to choose the distribution that fit the data the best. The probability distributions include Cauchy, Error, Hypersequent, Gamma, Laplace, Logistic, Log Pearson 3, Rayleigh (2p), Weibull (3p), Log Logistic (3p), Triangular, Gen. Gamma, Gen. Gamma (4p), Gen. Extreme Value, Log Normal (3p), Log Pearson 5, Fatigue life (3p), Inv. Gaussian (3p), and Nakagami.

Keywords: Anderson-darling test; Cauchy; Chi-square test; Distribution fitting; Fatigue life(3p); Gamma (3p); Generalized Extreme Value; Goodness-of-fit; Inverse Gaussian; Kolmogorov-Smirnov test; Laplace; Log Logistic; Log Pearson 3; Probability Distribution (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejmath:v:4:y:2023:i:2:id:14179

DOI: 10.24018/ejmath.2023.4.2.179

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