The efficiency of multiple imputation and maximum likelihood methods for estimating missing values

Montshiwa, Volition Tlhalitshi; Moroke, Ntebogang Dinah; Munapo, Elias

doi:10.17485/ijst/2018/v11i16/118701

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…The distribution of the Kolmogorov's goodness-of-fit measure D n has been studied in many articles [28], [29], [30]. It was shown that D n distribution is independent of the theoretical distribution (F).…”

Section: Comparison Of Vg Modelsmentioning

confidence: 99%

Fitting Infinitely divisible distribution: Case of Gamma-Variance Model

Nzokem

2021

Preprint

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The paper examines the Fractional Fourier Transform (FRFT) based technique as tools for obtaining the probability density function and its derivatives; and broadly for fitting stochastic model with the fundamental probabilistic relationships of infinite divisibility. The probability density functions are computed and the distributional proprieties such as leptokurtosis, peakedness, and asymmetry are reviewed for Variance-Gamma (VG) model and Compound Poisson with Normal Compounding model. The first and second derivatives of probability density function of the VG model are also investigated. The VG model has been increasingly used as an alternative to the Classical Lognormal Model (CLM) in modelling asset price. The VG model with fives parameters was estimated by the FRFT. The data comes from the SPY historical data, the SPDR S&P 500 ETF (SPY). The Kolmogorov-Smirnov (KS) goodness-of-fit shows that the VG model fits better the cumulative distribution of the sample data than the CLM. The best VG model comes from the FRFT estimation.

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Section: Comparison Of Vg Modelsmentioning

confidence: 99%