Inference for Noisy Samples

Abstract

In the current work, some well-known inference procedures including testing and estimation are adjusted to accommodate noisy data that lead to nonidentically distributed sample. The main two cases addressed are the Poisson and the normal distributions. Both one and two sample cases are addressed. Other cases including the exponential and the Pareto distributions are briefly mentioned. In the Poisson case, the situation when the sample size is random is mentioned.