🔭 In #RadioAstronomy, image formation is usually framed as reconstructing a nonnegative function from sparse #Fourier data. This study explores estimating a diagonal covariance matrix from #GaussianData using iterative #MaximumLikelihood methods. 📖 https://t.co/hs7Hondqc3

🏥 This study evaluates 4 models for multi-population #MortalityProjection to assess COVID-19’s long-term impact. 📌 #GAM–#APC model best predicts long-term trends, guiding #StrategicPlanning & #DecisionMaking amid uncertain mortality futures. 👉 https://t.co/bl9UNU6ykm

🔍 In this article, two groups are brought onto a common metric using the 2-Parameter Logistic model (#2PL). ✅ A bias-corrected linking error improves total #ErrorEstimation & inference. 📖 https://t.co/gPRmqRnOQc

🔍 Explore the future of #HumanDataScience! Stats launches a new Special Issue (Ed. Prof. Dr. Changgyun Kim) on human-generated data, combining #stats, #MachineLearning / #DeepLearning & human-centered analytics. 📖 Details: https://t.co/f1YlSByFPJ

💉 People who inject #drugs face higher #HIV risk. 👥 Using data from 277 participants, researchers found medications for #OpioidUseDisorder may reduce injection risk behaviors across connected communities. 📖 Read more: https://t.co/IhIYjLExIi

🌎 This study on #earthquake seismicity in Central & South America analyzed 10 #SeismicZones. 🔍 Probabilities of earthquake occurrence evaluated using #HiddenMarkovModel + #EMalgorithm. 📖 Read more: https://t.co/3IPbuzxMQX

📖Read more about #CopulaABCdrf, a new Approximate Bayesian Computation framework that unifies and extends previous ABC methods to estimate posterior distributions and MLEs for models with intractable likelihoods. https://t.co/4NOLO0BqML #BayesianInference #Stats

☕ This study integrates choice experiments, sensory tests, & HPLC caffeine analysis to explore coffee consumers’ perceptions before and after guided tastings. Bayesian optimal design + Random Utility Models reveal key behavioral insights! 📖 Read more: https://t.co/V5FduinR1l

🇬🇧🇪🇺Political events play a significant role in exerting their influence on financial markets globally. This paper aims to investigate the long term effect of #Brexit on #EuropeanStockMarkets using #ComplexNetwork methods as a starting point. 💥Read: https://t.co/NktuKqZBXO

🔍 New study proposes a #Bayesian zero-inflated model to improve #PatentKeywordAnalysis in highly sparse patent–keyword matrices. Applied to digital therapeutics patents, the method shows improved performance in #BigData & #MachineLearning contexts. 📖 https://t.co/x3pZrCpNnS

📉 This #Python code uses #networkX implements configuration models & #NewmanRewiring for #ScaleFreeNetworks & assortative correlations. Tested on random hubs & applied to #BassDiffusionModel for diffusion peak timing. 📖 Read more: https://t.co/ikCyTVPp1W

🔺 The #EURegionalCompetitivenessIndex 2.0 highlights challenges in Southern & Eastern EU regions. This study dives deeper with a county-level analysis of Romania & Bulgaria, examining labor, health, transport, tourism etc. 📖 https://t.co/jp7Ni06M6E #RegionalDevelopment #NUTS3

🌊Lack of flood data limits #FloodManagement. This study uses #GANs to generate synthetic flood events that follow physical laws—boosting #FloodForecasting accuracy. 🌧️📈 📖 Read: https://t.co/YTWiQsfj4D

📉 It was believed binary 0–1 #Bernoulli variables can’t show #ExtraBinomialVariation. But #Hilbe challenged this. This paper uncovers hidden variance, showing it arises from an underlying #Beta variable rounded to Bernoulli, masking extra variation. https://t.co/k5QOahQgja

🔍 Can we combine #ActiveLearning (AL) with #EnsembleLearning to boost performance and cut costs? This paper proposes AL algorithms numerically illustrated with the #SupportVectorMachine model using simulated data and two real-world applications. 📖 https://t.co/d2JGpcmLMv

📉 #ChangePointDetection in #TimeSeries omics data is key to understanding dynamic biological systems, but high-dimensional data makes it tricky. This paper introduces a Pearson-like #ScaledBregmanDivergence approach that boosts accuracy & stability! 📖 https://t.co/Cq7ufQYKGp

🔺 The #KumaraswamyDistribution is a powerful alternative to the Beta distribution on (0,1), widely used in both theoretical and #AppliedStatistics. 📉 This study applies biased transformation to classic #GoodnessOfFit tests. 📖 Read more:

This paper proposes a #PhylogeneticRegressionModel to study trait evolution. 🌱 📊 Developed by phylogenetic network in #eNewick format. 🌻 Applied to Helianthus annuus (sunflower) for drought response traits. 🔗 https://t.co/N1pXUMxrFC

📌Computing cross-partial #derivatives using fewer model runs is relevant in #modeling. This paper introduces surrogates of all the cross-partial derivatives of functions by evaluating functions at N randomized points and using a set of L constraints. https://t.co/tqMil8jbIH

📉 Research evaluates 4 models for multi-population #mortality projection to forecast #COVID19 impact. Using data from 5 countries, the #GAM-APC model proved most accurate for future mortality trends. Read more: https://t.co/ZFvSjRYBXt