This paper considers the problem of estimating the cumulative distribution function and probability density function of a random variable using data quantized by uniform and non-uniform quantizers. A ...

Traditional asymptotic analysis techniques fail for lognormal random variables (RV) because a lognormal probability density function cannot be quantified by Taylor series at the origin, and the moment ...

Typically, MADs are derived using the probability density functions (PDFs). By contrast, we derive simple expressions in terms of the integrals of the cumulative distribution functions (CDFs). We show ...

Various properties of the new distribution were derived, using the baseline beta distribution, statistical techniques, and probabilistic axioms. These include the probability density, cumulative ...

Discover the UMVUE for the gamma cumulative distribution function with known and integer scale parameters. Apply the Rao-Blackwell and Lehmann-Scheffeé Theorems for unbiased estimation. Explore an ...

Generative models are an important subset of machine learning goals and tasks that require realistic and statistically accurate generation of target data. Among all available generative models, ...

Abstract The purpose of this paper is to introduce a size biased Lindley distribution which is a special case of weighted distributions. Weighted distributions have practical significance where some ...