Sujit Sahu

Sujit Sahu

Professor of Statistics

University of Southampton

Biography

Sujit Sahu is a Professor of Statistics at the University of Southampton. He is the author of the book Bayesian modeling of spatio-temporal data with R.

Download his resumΓ©.

Interests
  • Bayesian modeling
  • Bayesian computation
  • Spatio-temporal data modeling
Education
  • PhD in Statistics, 1994

    University of Connecticut

  • Master of Statistics, 1989

    Indian Statistical Institute

Experience and Employment

Supervision Record, Experience and Employment history

Post-graduate Supervision

Here is a list of all my past post-docs, PhD and MSc students.

Research Grants Obtained

Education and Experience

Educational Qualifications and Experience.

Employment History

 
 
 
 
 
University of Southampton
Professor, Senior Lecturer and Lecturer in Statistics
Sep 1999 – Present Southampton, UK
 
 
 
 
 
Cardiff University
Lecturer in Statistics
Jan 1997 – Aug 1999 Cardiff
 
 
 
 
 
University of Cambridge
Research Associate
Mar 1994 – Dec 1996 Cambridge

R package ‘bmstdr’

The package source is available from github.

  • You can download this R file and install the package as instructed in it.
  • Or you can install directly in R from the commands given below.
  1. Windows binary of bmstdr: bmstdr_0.1.2.zip. Use the R command:
    install.packages("htps://www.sujitsahu.com/bmbook/bmstdr_0.1.2.zip", repos=NULL)
    
  2. Macos binary of bmstdr: bmstdr_0.1.2.tgz. Use the R command:
    install.packages("https://www.sujitsahu.com/bmbook/bmstdr_0.1.2.tgz", repos=NULL)
    
  3. Linux (Ubuntu) binary of bmstdr: bmstdr_0.1.2_R_x86_64-pc-linux-gnu.tar.gz. Use the R command:
    install.packages("https://www.sujitsahu.com/bmbook/bmstdr_0.1.2_R_x86_64-pc-linux-gnu.tar.gz", repos=NULL)
    

Source version of the package can be installed from github using the R command:

devtools::install_github("sujit-sahu/bmstdr", build_vignettes = TRUE)

Here is a copy of the bmstdr package vignette.

Teaching page

Welcome to Math1024: Intro to Probability and Stats.

Practical examples:

  1. Number of Covid-19 deaths per million people upto September 4, 2020.

    global trend
  2. Growth of the epidemic in selected countries.

    global trend

Contact