Nonparametric Methods for Practitioners: Theory with Applications in R
Instructor: Jeffrey S. Racine, Professor, McMaster University, Canada.
Topics covered by ASSEE 2018 included
- Density estimation (conditional and unconditional)
- Conditional mean estimation
- Conditional quantile estimation
- Conditional volatility estimation
- Panel data models (fixed and random effects)
- Using R and R markdown for reproducible research
This course introduced attendees to recent developments in semi- and nonparametric statistical and econometric methods. The emphasis was on kernel-based approaches.
The course was held over a five-day period and the format consisted of formal lectures in the morning for three hours per day, then there was a two-hour computer lab in the afternoon where attendees gained hands-on experience by working through a set of assignments that involved a set of popular datasets and topics. No prior experience in nonparametric methods nor exposure to the R software environment for statistical computing and graphics is presumed.
Attendees are expected to bring a laptop computer and all necessary software is free and open source. Attendees will receive advice on software installation prior to arriving at the course venue. Recent developments in tools for conducting reproducible research will be integrated into the course. A course website will contain all necessary material. Hardcopies of the lecture slides will be provided.