activity
20172022
collaborators

8 papers

stat.ME2022

Combining Data from Surveys and Related Sources

Dexter Cahoy, Joseph Sedransk

To improve the precision of inferences and reduce costs there is considerable interest in combining data from several sources such as sample surveys and administrative data. Approp…

stat.AP2022

Bayesian inference for asymptomatic COVID-19 infection rates

Dexter Cahoy, Joseph Sedransk

To strengthen inferences meta analyses are commonly used to summarize information from a set of independent studies. In some cases, though, the data may not satisfy the assumptions…

math.PR2020

Flexible models for overdispersed and underdispersed count data

Dexter Cahoy, Elvira Di Nardo, Federico Polito

Within the framework of probability models for overdispersed count data, we propose the generalized fractional Poisson distribution (gfPd), which is a natural generalization of the…

stat.ME2018

Estimation of Mittag-Leffler Parameters

Dexter Cahoy

We propose a procedure for estimating the parameters of the Mittag-Leffler (ML) and the generalized Mittag-Leffler (GML) distributions. The algorithm is less restrictive, computati…

stat.ME2018

Parameter estimation for fractional Poisson processes

Dexter Cahoy, Vladimir V. Uchaikin, Wojbor A. Woyczynski

The paper proposes a formal estimation procedure for parameters of the fractional Poisson process (fPp). Such procedures are needed to make the fPp model usable in applied situatio…

stat.ME2018

A bootstrap test for equality of variances

Dexter Cahoy

We introduce a bootstrap procedure to test the hypothesis that variances are homogeneous. The procedure uses a variance-based statistic, and is derived from a normal-th…