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Call For Papers
The ICATSFM is committed to addressing global challenges through impactful research and sustainable solutions. It brings together researchers dedicated to advancing knowledge for societal benefit.
Focusing on Statistics, Data Science, the conference promotes research aligned with global development goals and long-term sustainability.
Authors are invited to submit papers addressing, but not limited to, the following areas:
01
Time series forecasting methods and applications
02
Statistical modeling of temporal data
03
Seasonal decomposition in time series analysis
04
ARIMA models for time series forecasting
05
Statistical methods for financial time series
06
Time series analysis in environmental studies
07
Machine learning techniques for time series
08
Statistical methods for anomaly detection in time series
09
Longitudinal data analysis techniques
10
Statistical software for time series analysis
11
Causal inference in time series data
12
Applications of time series in public health
13
Statistical challenges in high-frequency data
14
Time series regression modeling approaches
15
Forecasting with multivariate time series
16
Statistical methods for economic time series
17
Time series analysis in social sciences
18
Bayesian approaches to time series forecasting
19
Statistical techniques for real-time forecasting
20
Future directions in time series analysis
Assessment
All submissions will be reviewed for their contribution to global impact and research quality. Accepted papers will be presented and considered for publication in reputed platforms.
Registration
Join participants from around the world by completing your registration and becoming part of a global research community.
Publication
Accepted papers will gain international exposure through conference presentations and publication opportunities.
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