Unbiased estimation of the autocovariance function in a stationary generalized lognormal process

Abstract

Let [Y_t], t = 0, ±1, ±2, …, be a stationary sequence of normally distributed random variables with means, μ variances σ² and autocorrelation coefficients ρ_h, h = 0, ±1, ±2, …, and let f be a recursive-type function. A stationary generalized lognormal porcess is defined as the sequence of {f(Y_t)], t = 0, ±1, ±2, …. The paper provides unbiased estimators for the autocovariance function of a stationary generalized lognormal process with known μ and unknown σ² and ρ_h Thier variances are also given.

Keywords:

• recursive-type function
• normalizing transformation
• variarces of estimators