Advanced Time Series Analysis with R
Siti Zulaikha
A skilled and dedicated trainer with expertise in data analytics, statistical modeling, and programming tools, this professional brings a practical, learner-focused approach to every session. With experience delivering training across diverse industries and academic levels, they specialize in simplifying complex concepts and equipping participants with real-world, job-ready skills. Known for their interactive teaching style and up-to-date knowledge of tools like Python, R, Power BI, and Stata, this trainer is committed to building data literacy and fostering continuous learning among individuals and teams alike.
Training Outline
Wavelet analysis and multiscale decomposition of time series
Transfer Entropy for detecting directional causality
Spatial and Graph-based time series methods
Quantile Coherence for dependency analysis across quantiles
Quantile-on-Quantile Regression (QQR) and Quantile Granger (QG)
Markov Switching Regression and MS-GARCH models
Diebold-Yilmaz (DY) Spillover Index for connectedness analysis
Cross-Quantilogram Correlation (CQC) for tail-dependent relationships
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