On the goodness-of-fit procedure for normality based on the empirical characteristic function for ranked set sampling data

The Split-SV model

“…After that, Leonenko (2009) andTaufer et al (2011) used this method in the estimation of non-Gaussian OU processes and OU-based SV models. Finally, some new extensions of the CF-based estimations in finance can be found in Kotchoni (2012) or Tsionas (2012), and some new theoretical extensions are given in Balakrishnan et al (2013), Meintanis et al (2013) and Kotchoni (2014).…”

Two new estimators of entropy for testing normality

“…The most recent one appears to be Balakrishnan et al (2013) [3], where they also considered the version of RSS Kolmogorov-Smirnov (D * ). For the comparison, we evaluate corresponding powers of the test statistics D * and S ( which introduced by Balakrishnan et al [3]), T V E R mn and T W R mn by means of Monte Carlo simulations for 8 different alternative distributions. These alternatives were used by Balakrishnan et al [3] as power comparison of several tests for normality.…”

“…For the comparison, we evaluate corresponding powers of the test statistics D * and S ( which introduced by Balakrishnan et al [3]), T V E R mn and T W R mn by means of Monte Carlo simulations for 8 different alternative distributions. These alternatives were used by Balakrishnan et al [3] as power comparison of several tests for normality. Table 13 contains the results of 10000 simulations (of samples size 25,30,45,50,60,75,90 and 100) per case to obtain the power of the proposed tests and those of the competitor tests, at significance level α = 0.05.…”

“…Balakrishnan and Li [4] proposed ordered ranked set sampling (ORSS) and developed optimal linear inference based on ORSS. Recently, Balakrishnan et al [3] considered the goodness-of-fit procedure for testing normality based on the empirical characteristic function for ranked set sampling data. A very well written and complete overview of the available results in the context of RSS is the book of Chen et al [7], which includes 175 key references on this subject.…”

Nonlinear stochastic modelling dynamic of the agricultural products exchange rates

“…Later, in 1986, Tim Bollerslev (Bollerslev, 1986) defined the so-called Generalized Autoregressive Conditional Heteroskedastic models (GARCH models) with the ARCH models as a conceptual basis. These models have been further modified and are still in use today (Balakrishnan et al, 2013).…”