Results 51 to 60 of about 18,517 (245)
Strictly frequentist imprecise probability
Strict frequentism defines probability as the limiting relative frequency in an infinite sequence. What if the limit does not exist? We present a broader theory, which is applicable also to random phenomena that exhibit diverging relative frequencies.
Christian Fröhlich +2 more
openaire +4 more sources
Continuous outcome estimation in N‐of‐1 trials for accelerated decision‐making
Abstract Objective N‐of‐1 trials aim to determine the therapeutic effect for a single individual. This individualized approach necessitates collecting multiple data points over time through repeated alternating periods of active treatment and a comparator or control condition.
Victoria Defelippe +5 more
wiley +1 more source
A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley +1 more source
Bayesian versus Frequentist approaches in Psychometrics: a bibliometric analysis
The increasing popularity of the Bayesian approach in Psychology has prompted metascientific efforts to quantify its prevalence. However, despite enduring debates between proponents of Frequentist and Bayesian schools of thought, no systematic comparison
Andrea Zagaria, Luigi Lombardi
doaj +1 more source
Predictive P-score for treatment ranking in Bayesian network meta-analysis
Background Network meta-analysis (NMA) is a widely used tool to compare multiple treatments by synthesizing different sources of evidence. Measures such as the surface under the cumulative ranking curve (SUCRA) and the P-score are increasingly used to ...
Kristine J. Rosenberger +3 more
doaj +1 more source
Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach
ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch +3 more
wiley +1 more source
The Johnstone's whistling frog is an invasive species whose loud night‐time calls may affect human health and well‐being. Our study in Cali, Colombia, combined fieldwork and online surveys to assess its urban occupancy, density, and potential health impacts.
Rubén Darío Palacio, Sumana Goli
wiley +1 more source
Abstract Background Adolescence is marked by increased vulnerability to sleep disturbances and mood disorders. Understanding how day‐to‐day changes in sleep and mood are linked within the same individual is crucial for clarifying sleep's role in emerging internalizing disorders. However, the extent to which an adolescent's fluctuations in sleep predict
Konstantin Drexl +4 more
wiley +1 more source
Background Random effects modelling is routinely used in clustered data, but for prediction models, random effects are commonly substituted with the mean zero after model development.
Haifang Ni +3 more
doaj +1 more source
Estimating water resources is important for regional climate impact analysis and risk estimation. The Middle East and Central Asia have largely reached the limit of sustainably usable water across their river basins and ecosystems. Strategies designed to mitigate environmental risks require a reliable estimation of water availability trends.
Paolo Reggiani +4 more
wiley +1 more source

