E. Dreassi

activity

20132026

most citedDisease Mapping via Negative Binomial Regression M-quantiles

33 citations · 34 across the 9 of their papers we have counts for

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Showing math.STShow all

5 papers · 1 filter

math.ST2026

Some cautionary tales about Bayesian predictive inference

Emanuela Dreassi, Fabrizio Leisen, Luca Pratelli +1

Two misunderstandings, frequently arising in Bayesian predictive inference, are discussed. The first deals with the data generating mechanism, while the second consists in overesti…

math.ST2024

Knockoffs for exchangeable categorical covariates

Emanuela Dreassi, Luca Pratelli, Pietro Rigo

Let $X = (X_{1}, \dots, X_{p})$ be a $p$ -variate random vector and $F$ a fixed finite set. In a number of applications, mainly in genetics, it turns out that $X_{i} \in F$ for each $i=1,\ldo…

math.ST2022

Generating knockoffs via conditional independence

Emanuela Dreassi, Fabrizio Leisen, Luca Pratelli +1

Let $X$ be a $p$ -variate random vector and $X$ a knockoff copy of $X$ (in the sense of \cite{CFJL18}). A new approach for constructing $X$ (henceforth, NA)…

math.ST2021

Bayesian predictive inference without a prior

Patrizia Berti, Emanuela Dreassi, Fabrizio Leisen +2

Let $(X_{n} : n \geq 1)$ be a sequence of random observations. Let $σ_{n} (\cdot) = P (X_{n + 1} \in \cdot ∣ X_{1}, \dots, X_{n})$ be the $n$ -th predictive distribution and $σ_0(\cdot)=P(X_…

math.ST2021

New perspectives on knockoffs construction

Patrizia Berti, Emanuela Dreassi, Fabrizio Leisen +2

Let $Λ$ be the collection of all probability distributions for $(X, X)$ , where $X$ is a fixed random vector and $X$ ranges over all possible knockoff copies…