Quasi-randomization approaches estimate latent participation probabilities for units from a nonprobability / convenience sample. Estimation of participation probabilities for convenience units allows their combination with units from the randomized survey sample to form a survey-weighted domain...

We propose a flexible, extensible family of distributions for testing Markov Chain Monte Carlo implementations. Distributions are created by nesting simple transformations, which allow various shapes, including multiple modes and fat tails. The resulting distributions can be sampled with high...

Reasonably pricing data resources contributes to the development of the digital economy. However, in the early stage of the development of the data market, the data transaction volume is small, and the resulting small sample problem makes it difficult to accurately model and forecast the price...

Nonprobability (convenience) samples are increasingly sought to reduce the estimation variance for one or more population variables of interest that are estimated using a randomized survey (reference) sample by increasing the effective sample size. Estimation of a population quantity derived...