Data Science in Science
@DataSciScience
OA journal publishing original research and reviews at the intersection of #Science & #DataScience. Affiliated journal of the American Statistical Association.
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Great news! Data Science in Science has been accepted into Scopus! @tandfSTEM #Scopus #DataScience
Dynamic Linear Models for Wastewater-Based Epidemiology with Missing Values: an Application to Covid-19 Surveillance @tandfSTEM #epidemiology #data #water #covid19 tandfonline.com/doi/full/10.10…
tandfonline.com
Dynamic Linear Models for Wastewater-Based Epidemiology with Missing Values: an Application to...
We argue for the usage of dynamic linear models (DLMs) for pre-processing and modeling of wastewater data used for surveillance of population infectious disease levels. Unlike other existing models...
A Nonlinear Hierarchical Time Series Approach to Citywide Trend Assessment of Viruses, Hot Spot Signals, and Right-Sizing System tandfonline.com/doi/full/10.10…
tandfonline.com
A Nonlinear Hierarchical Time Series Approach to Citywide Trend Assessment of Viruses, Hot Spot...
Wastewater surveillance has proven to be a cost-effective cornerstone in public health, offering vital insights into a spectrum of community health issues, particularly during the COVID-19 pandemic...
New Journal alert - ASA Discoveries! New OA journal from the American Statistical Association and published by @tandfonline @tandfSTEM Check out the opening Editorial below! ⬇️⬇️⬇️⬇️⬇️⬇️⬇️ tandfonline.com/doi/full/10.10…
On Some Test Statistics for Coefficients in the Ridge, Liu and Kibria–Lukman Linear Regression Models: A Simulation Study tandfonline.com/doi/full/10.10…
tandfonline.com
On Some Test Statistics for Coefficients in the Ridge, Liu and Kibria–Lukman Linear Regression...
Ridge, Liu, and Kibria–Lukman regression methods that have been proposed to solve the multicollinearity problem for both linear and generalized linear regression models (Kibria and Lukman, Shewa an...
Designing Efficient Sample Strata Through Application of Random Forest Classifiers to Administrative and Survey Data tandfonline.com/doi/full/10.10…
tandfonline.com
Designing Efficient Sample Strata Through Application of Random Forest Classifiers to Administrat...
Surveys aiming to oversample certain classes of households to reduce the variance of estimates for small subgroups typically randomly oversample units in geographies where the characteristic(s) of ...
Echo State Networks for Spatio-Temporal Area-Level Data tandfonline.com/doi/full/10.10…
tandfonline.com
Echo State Networks for Spatio-Temporal Area-Level Data
Spatio-temporal area-level datasets play a critical role in official statistics, providing valuable insights for policy-making and regional planning. Accurate modeling and forecasting of these data...
SeasCen, A Python-Based Platform for Time Series Modeling and Seasonal Adjustment tandfonline.com/doi/full/10.10…
tandfonline.com
SeasCen, A Python-Based Platform for Time Series Modeling and Seasonal Adjustment
Whereas X-13ARIMA-SEATS (X-13) is widely used around the world to seasonally adjust economic time series, its continued longevity is jeopardized by the ongoing difficulty of maintaining its FORTRAN...
Causal Risk Ratio and Causal Risk Difference in Longitudinal Studies With Frequent Outcome Events tandfonline.com/doi/full/10.10…
tandfonline.com
Causal Risk Ratio and Causal Risk Difference in Longitudinal Studies With Frequent Outcome Events
Marginal structural models (MSMs) are recognized as useful methods for addressing the issue of time-varying confounding in longitudinal studies. In the analyses of longitudinal data with binary out...
Multi-Regime Smooth Transition Stochastic Volatility Models for Financial Time Series tandfonline.com/doi/full/10.10…
tandfonline.com
Multi-Regime Smooth Transition Stochastic Volatility Models for Financial Time Series
Stochastic volatility (SV) models effectively capture the time-varying variance in financial time series, and regime-switching SV models further enhance flexibility by adapting to changing market c...
New article: A Bayesian Time-Varying Psychophysiological Interaction Model @tandfSTEM tandfonline.com/doi/full/10.10…
tandfonline.com
A Bayesian Time-Varying Psychophysiological Interaction Model
Functional connectivity, the study of coordination between distinct brain regions, is a key focus in neuroscience. The Psychophysiological Interaction (PPI) model, commonly used to infer task-depen...
Uncovering Dynamic Relationships Between SARS-CoV-2 Wastewater Concentrations and Community Infections via Bayesian Spatial Functional Concurrent Regression tandfonline.com/doi/full/10.10…
THANOS: A Predictive Model of Electoral Campaigns Using Twitter Data and Opinion Polls tandfonline.com/doi/full/10.10…
tandfonline.com
THANOS: A Predictive Model of Electoral Campaigns Using Twitter Data and Opinion Polls
The influence and impact of social media campaigns on democratic elections is a critical area of research in modern big-data analytics. While the efficacy of using social media data for forecasting...
A Novel Tree-Based Combined Test for Seasonality tandfonline.com/doi/full/10.10…
tandfonline.com
A Novel Tree-Based Combined Test for Seasonality
Conducting routine seasonal adjustments of economic data has been an important responsibility of federal statistical agencies for decades. Since those adjustments typically include regular checks f...
Building the Census Bureau Index of Economic Activity (IDEA) tandfonline.com/doi/full/10.10…
tandfonline.com
Building the Census Bureau Index of Economic Activity (IDEA)
The Census Bureau Index of Economic Activity is constructed from 15 of the Census Bureau’s primary monthly economic indicators to provide a single time series reflecting the variation over time in ...
Free Webinar - sign up now! Apr 22, 2025 - "Escape the Crop Circle Conundrum" @maanow @tandfSTEM #Scatterplot #mathematics #DataScience bit.ly/43DyyzJ
THANOS: A Predictive Model of Electoral Campaigns Using Twitter Data and Opinion Polls tandfonline.com/doi/full/10.10…
tandfonline.com
THANOS: A Predictive Model of Electoral Campaigns Using Twitter Data and Opinion Polls
The influence and impact of social media campaigns on democratic elections is a critical area of research in modern big-data analytics. While the efficacy of using social media data for forecasting...
Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms tandfonline.com/doi/full/10.10…
tandfonline.com
Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms
We propose a Bayesian covariate-dependent anti-logistic circadian model for analyzing activity data collected via wrist-worn wearable devices. The proposed approach integrates covariates into the m...
Emerging Neuroimaging Approach of Hybrid EEG-fNIRS Recordings: Data Collection and Analysis Challenges tandfonline.com/doi/full/10.10…
tandfonline.com
Emerging Neuroimaging Approach of Hybrid EEG-fNIRS Recordings: Data Collection and Analysis...
The hybrid EEG-fNIRS (electroencephalogram - functional near-infrared spectroscopy) modality provides a comprehensive understanding of brain activity by simultaneously capturing electrical and hemo...
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