On the Equivalence of the Coefficient of Variation Ordering and the Lorenz Ordering Within Two-Parameter Families

Here we develop the uniformly minimum variance unbiased (best) estimators of coefficient of variation, Pearson's coefficients of skewness and kurtosis of two-parameter Pareto distribution, the variance of these best estimators and the best estimators of those variances. The best estimators are in terms of Kummer's function 1 F1 and Humbert's function ø2 ; and their variances are in terms of F2 , the Appel function of second kind and K 12 , a quadruple hypergeornetric function invented by Exton during the early 1970's.

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A new three-parameter size-biased poisson-lindley distribution with properties and applications

Biometrics & Biostatistics International Journal ◽

10.15406/bbij.2020.09.00294 ◽

2020 ◽

Vol 9 (1) ◽

pp. 1-4

Author(s):

Rama Shanker ◽

Kamlesh Kumar Shukla

Keyword(s):

Maximum Likelihood ◽

Maximum Likelihood Estimation ◽

Negative Binomial Distribution ◽

Coefficient Of Variation ◽

Goodness Of Fit ◽

Negative Binomial ◽

Geometric Distribution ◽

Likelihood Estimation ◽

Lindley Distribution ◽

Two Parameter

A new three-parameter size-biased Poisson-Lindley distribution which includes several one parameter and two-parameter size-biased distributions including size-biased geometric distribution (SBGD), size-biased negative binomial distribution (SBNBD), size-biased Poisson-Lindley distribution (SBPLD), size-biased Poisson-Shanker distribution (SBPSD), size-biased two-parameter Poisson-Lindley distribution-1 (SBTPPLD-1), size-biased two-parameter Poisson-Lindley distribution-2(SBTPPLD-2), size-biased quasi Poisson-Lindley distribution (SBQPLD) and size-biased new quasi Poisson-Lindley distribution (SBNQPLD) for particular cases of parameters has been proposed. Its various statistical properties based on moments including coefficient of variation, skewness, kurtosis and index of dispersion have been studied. Maximum likelihood estimation has been discussed for estimating the parameters of the distribution. Goodness of fit of the proposed distribution has been discussed.

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Some results of the Barbier-Chalonge-Divan system of stellar classification

Symposium - International Astronomical Union ◽

10.1017/s0074180900053250 ◽

1966 ◽

Vol 24 ◽

pp. 77-90 ◽

Cited By ~ 1

Author(s):

D. Chalonge

Keyword(s):

Early Type ◽

Parameter System ◽

Early Type Stars ◽

Two Parameter

Several years ago a three-parameter system of stellar classification has been proposed (1, 2), for the early-type stars (O-G): it was an improvement on the two-parameter system described by Barbier and Chalonge (3).

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Subjective Time Preference and Willingness to Pay for an Energy-Saving Durable Good

Zeitschrift für Sozialpsychologie ◽

10.1024//0044-3514.32.3.133 ◽

2001 ◽

Vol 32 (3) ◽

pp. 133-141 ◽

Cited By ~ 4

Author(s):

Gerrit Antonides ◽

Sophia R. Wunderink

Keyword(s):

Willingness To Pay ◽

Energy Saving ◽

Subjective Time ◽

Durable Good ◽

Discount Function ◽

Hyperbolic Discount ◽

The One ◽

Two Parameter ◽

Difference Effect ◽

Better Than

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.

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