A major goal in recurrent events analysis is to estimate the bivariate distribution function. This estimation is crucial across various fields and applications, as it helps clarify the patterns of recurring events and their underlying patterns. ‘Gap time’ refers to the duration between consecutive occurrences of an event, while the bivariate distribution function represents the joint probability distribution of...
This study examines the impact of climate investment policies on citizens’ perception of pollution damage in the European Union, while controlling for various environmental indicators. The primary panel data estimation outcome indicates that, despite substantial public expenditure on climate action, consumers’ perception of pollution improvement remains unchanged or even worsens. This suggests support for the p...
We analyze a two-sided market where two platforms compete in electricity intraday trading. These intermediaries are differentiated both vertically and horizontally and engage in price competition to attract agents from both sides of the market, buyers and sellers. Alongside accounting for quality disparities at the intermediary level, we consider the possibility that platforms may choose to customize electricit...
There is a substantial demand for user-friendly graphical interfaces that empower professionals with limited programming knowledge to perform statistical analysis. Although R software is widely used for statistical analysis, it lacks an adequately intuitive graphical interface for individuals without statistical and programming skills. This paper aims to address this gap by introducing an application called Sur...
In many fields, including medical research, engineering, and the social sciences, analyzing time-to-event data is essential for uncovering underlying processes and facilitating decision-making. A common challenge in this analysis arises when events are confirmed to have taken place within specific time intervals, yet the exact timing within those intervals remains unknown, a phenomenon known as interval censori...
A main objective in recurrent event analysis is the estimation of the bivariate distribution function. This estimation is crucial across various fields, as it helps to better understand the patterns of recurring events and their underlying dynamics. The term ’gap time’ refers to the interval between consecutive occurrences of an event, and the bivariate distribution func- tion captures the joint probability dis...
Multi-state models are essential tools in longitudinal data analysis, enabling the estimation of transition probabilities that provide predictive insights into clinical outcomes across stages of disease progression or recovery. Conventional approaches to inference in these models often rely on the Markov assumption, which simplifies computation but may not hold in complex real-world settings. To address this li...
This work is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., under the UID/00013: Centro de Matemática da Universidade do Minho (CMAT/UM) Program Contract, and the project reference 2023.14897.PEX (DOI: 10.54499/2023.14897.PEX).; Interval-censored data frequently arise in survival analysis when the exact time of an event is unknown but is known to occur within a specific tim...
This work is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., under the UID/00013: Centro de Matemática da Universidade do Minho (CMAT/UM) Program Contract, and the project reference 2023.14897.PEX (DOI: 10.54499/2023.14897.PEX).; Handling interval-censored data in survival analysis presents signi cant challenges, as the exact time to the event is only known to fall within pr...
The development of applications aimed at providing interpretable results in a concise and user-friendly manner within the framework of multi-state models represents a promising research avenue, particularly when leveraging open-source tools adaptable to biomedical contexts. This paper introduces MSM.app, an interactive web application constructed using the Shiny package for the R language. MSM.app is structured...