A large number of exact inferential procedures in statistics and econometrics involve the sampling distribution of ratios of random variables. If the denominator variable is positive, then tail probabilities of the ratio can be expressed as those of a suitably defined difference of random...

This note discusses some problems possibly arising when approximating via MonteCarlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to reestimate unknown parameters on each simulated Monte-Carlo sample - and...

This paper analyzes the higher-order properties of nested pseudo-likelihood (NPL) estimators and their practical implementation for parametric discrete Markov decision models in which the probability distribution is defined as a fixed point. We propose a new NPL estimator that can achieve...

Correlation coefficients among multiple variables are commonly described in the form of matrices. Applications of such correlation matrices can be found in many fields, such as finance, engineering, statistics, and medicine. This article proposes an efficient way to sequentially obtain the...

Credit value adjustment (CVA) and related charges have emerged as important risk factors following the Global Financial Crisis. These charges depend on uncertain future values of underlying products, and are usually computed by Monte Carlo simulation. For products that cannot be valued...

Johan Gielis showed that all closed curves might be considered as some sort of deformed ellipses. He gave a superformula to parameterize such shapes. In this study an attempt has been made to estimate the parameters of Gielis' superformula from empirical data. We use an optimum search algorithm...

Ricardo Chacoacute;n generalized Johan Gielis's superformula by introducing elliptic functions in place of trigonometric functions. In this paper an attempt has been made to fit the Chacoacute;n-Gielis curves (modified by various functions) to simulated data. Estimation has been done by the...

A simple and readily computable algorithm is developed for approximating the low moments of order deviates from any continuous distribution. The results are compared with those obtained from exact closed form moments, obtained from quadrature as well as other non-Monte Carlo integral computations

This paper develops an unbiased Monte Carlo approximation to the transition density of a jump-diffusion process with state-dependent drift, volatility, jump intensity, and jump magnitude. The approximation is used to construct a likelihood estimator of the parameters of a jump-diffusion observed...

This paper proposes new estimation techniques for gravity models with zero trade values and heteroscedasticity. We propose various Heckman estimators with different distributions of the residuals, nonlinear forms of both selection and measure equations, and various process of the variance. We...