Registration summary
ConferenceICMPMSM
ModeStandard / Physical
ParticipationListener
Registration fee$175.00
Bank charges (5.8%)$10.15
Total payable$185.15
Includes all bank processing charges — the amount above is exactly what will be charged.
Benefits of Registering as Listener
Access to Conference Sessions
Networking Opportunities
Certificate of Participation
Invitation Letter Support
Conference Kit / Materials
Access to Keynote Sessions
• Conference Session Tracks •
SDG-Aligned Research Themes
ICMPMSM conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advancements in Multivariate Probability Theory +
This track focuses on recent developments in multivariate probability theory, emphasizing theoretical frameworks and innovative approaches. Contributions that explore the implications of multivariate distributions in various applications are particularly encouraged.
02 Statistical Methods for High-Dimensional Data +
This session will explore statistical methodologies tailored for high-dimensional datasets, including challenges and solutions in estimation and inference. Topics such as variable selection, regularization techniques, and model evaluation will be discussed.
03 Machine Learning Techniques in Statistical Analysis +
This track aims to bridge the gap between machine learning and traditional statistical methods, highlighting how these fields can complement each other. Papers that demonstrate the application of machine learning algorithms in statistical contexts are welcome.
04 Regression Analysis in Multivariate Contexts +
This session will delve into advanced regression techniques applicable to multivariate data, including generalized linear models and multivariate adaptive regression splines. Contributions that address model diagnostics and validation in complex scenarios are encouraged.
05 Clustering and Classification Techniques in Data Science +
This track will cover innovative clustering and classification methods that enhance data interpretation and decision-making. Emphasis will be placed on algorithmic advancements and their practical applications in various domains.
06 Dimension Reduction Techniques in Statistical Modeling +
This session will focus on dimension reduction methods, such as Principal Component Analysis and Factor Analysis, that facilitate the simplification of complex datasets. Papers that demonstrate the effectiveness of these techniques in real-world applications are encouraged.
07 Simulation Techniques in Probability and Statistics +
This track will explore the role of simulation in probability and statistical methods, including Monte Carlo simulations and bootstrapping. Contributions that showcase novel simulation techniques and their applications in empirical research are welcome.
08 Big Data Analytics: Challenges and Solutions +
This session will address the challenges posed by big data in statistical analysis and present innovative solutions. Topics may include data management, processing techniques, and the integration of statistical methods with big data technologies.
09 Computational Statistics: Methods and Applications +
This track will highlight computational approaches in statistics, focusing on algorithm development and implementation. Papers that discuss the application of computational methods in solving complex statistical problems are particularly encouraged.
10 Predictive Analytics in Multivariate Frameworks +
This session will explore the intersection of predictive analytics and multivariate statistical methods, emphasizing model development and validation. Contributions that demonstrate the application of predictive models in various fields are welcome.
11 Applications of Applied Statistics in Research +
This track will showcase the application of statistical methods in diverse research fields, highlighting case studies and empirical findings. Contributions that illustrate the impact of applied statistics on decision-making and policy formulation are encouraged.
