The following pages link to Alessio Farcomeni (Q85323):
Displaying 34 items.
- A discrete time event‐history approach to informative drop‐out in mixed latent Markov models with covariates (Q3465726) (← links)
- Generalized Augmentation to Control the False Discovery Exceedance in Multiple Testing (Q3552969) (← links)
- (Q3580583) (← links)
- A review of modern multiple hypothesis testing, with particular attention to the false discovery proportion (Q3597112) (← links)
- Wild adaptive trimming for robust estimation and cluster analysis (Q4629281) (← links)
- Latent class recapture models with flexible behavioural response (Q4965719) (← links)
- Robust Methods for Data Reduction (Q4982973) (← links)
- Directional Quantile Classifiers (Q5057099) (← links)
- Robust inference for parsimonious model-based clustering (Q5107332) (← links)
- Population size estimation with interval censored counts and external information: Prevalence of multiple sclerosis in Rome (Q5120955) (← links)
- Joint analysis of occurrence and time to stability after entrance into the Italian labour market: an approach based on a Bayesian cure model with structured stochastic search variable selection (Q5124945) (← links)
- A Multivariate Extension of the Dynamic Logit Model for Longitudinal Data Based on a Latent Markov Heterogeneity Structure (Q5252150) (← links)
- (Q5325304) (← links)
- Contribution to the discussion of the paper by Stefan Wellek: “A critical evaluation of the current <i>p</i>‐value controversy” (Q5364017) (← links)
- Penalized estimation in latent Markov models, with application to monitoring serum calcium levels in end‐stage kidney insufficiency (Q5364044) (← links)
- Some Results on the Control of the False Discovery Rate under Dependence (Q5430580) (← links)
- Information matrix for hidden Markov models with covariates (Q5963726) (← links)
- Comments on: ``Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination'' (Q5965749) (← links)
- A regularized MANOVA test for semicontinuous high-dimensional data (Q5978329) (← links)
- Continuous Time-Interaction Processes for Population Size Estimation, with an Application to Drug Dealing in Italy (Q6055878) (← links)
- An ensemble approach to short‐term forecast of COVID‐19 intensive care occupancy in Italian regions (Q6091715) (← links)
- Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers (Q6116606) (← links)
- Quantile ratio regression (Q6547762) (← links)
- A likelihood ratio test for completed sampling in population size estimation studies (Q6550320) (← links)
- A shared-parameter continuous-time hidden Markov and survival model for longitudinal data with informative dropout (Q6625720) (← links)
- Two years of COVID-19 pandemic: the Italian experience of statgroup-19 (Q6626514) (← links)
- Multistate quantile regression models (Q6627269) (← links)
- Nowcasting COVID-19 incidence indicators during the Italian first outbreak (Q6628159) (← links)
- Probabilistic principal component analysis to identify profiles of physical activity behaviours in the presence of non-ignorable missing data (Q6639104) (← links)
- Fully general Chao and Zelterman estimators with application to a whale shark population (Q6641379) (← links)
- Rectangular latent Markov models for time-specific clustering, with an analysis of the wellbeing of nations (Q6642078) (← links)
- PDE-regularised spatial quantile regression (Q6656677) (← links)
- A dynamic inhomogeneous latent state model for measuring material deprivation (Q6668764) (← links)
- Covariate-modulated rectangular latent Markov models with an unknown number of regime profiles (Q6669973) (← links)
