Resources

Books:

• Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA - Finn Lindgren
• Advances in heavy tailed risk modeling: A handbook of operational risk - Gareth Peters and Pavel V. Shevchenko
• An Introduction to Secondary Data Analysis with IBM SPSS Statistics - John MacInnes
• A Tiny Handbook on R - Mike Allerhand (review)
• Bayesian Analysis for Population Ecology - Ruth King
• Core Statistics - Simon Wood
• Fundamental aspects of operational risk and insurance analytics -  Gareth Peters, Marcelo G. Cruz and Pavel V. Shevchenko
• Gaussian Processes for Machine Learning - Chris Williams
• Generalized Additive Models - Simon Wood
• Know Your Variables: Little Quick Fix - John MacInnes
• Quantitative Longitudinal Data Analysis - Vernon Gayle
• Modern Methodology and Applications in Spatial-Temporal Modeling - Gareth Peters and Tomoko Matsui
• Monte Carlo and Quasi-Monte Carlo Methods 2012 - Gareth Peters et. al
• Statistical Significance: Little Quick Fix - John MacInnes
• Statistics and the Evaluation of Evidence for Forensic Scientists (3rd Ed.)- Colin Aitken
• Theoretical Aspects of Spatial-Temporal Modeling - Gareth Peters  and Tomoko Matsui

Special Issues:

• A Collection of Surveys on Tail Event Modeling, Revstat—Statistical Journal, Vol. 10, 2012, Guest Editors  - M. de Carvalho, A. C. Davison & J. Beirlant.
• Animal Movement Modeling, Journal of Agricultural, Biological, and Environmental Statistics, vol 22, issue 3, 2017 - Guest Editors Ruth King, Mevin B. Hooten, Roland Langrock
• European Young Statisticians, Communications in Statististics—Theory and Methods, vol 42, 2013, Guest Editors - M. de Carvalho & P. C. Rodrigues
• Modelling Key Variables in Social Science Research, Methodological Innovations, vol 9, 2016 - Roxanne Connelly, Vernon Gayle & Paul Lambert
• Statistical Models for Diagnosis and ROC Analysis (PDF), Revstat—Statistical Journal, vol 12, 2014 - Guest Editors - V. I. de Carvalho, M. de Carvalho & W. G. Manteiga
• Stochastic Simulation and Optimisation in Signal Processing, IEEE Journal of Special Topics in Signal Processing, vol 10, issue 2, 2016 - Guest Editors  -Steve Mclaughlin, Marcelo Pereyra, Alfred O. Hero, Jean-Yves Tourneret, Jean-Christophe Pesquet

• A short course on likelihood based inference - Course by Simon Wood
• Data Ethics, AI and Responsible Innovation  - A free online course from The University of Edinburgh
• Statistics: Unlocking the World of Data - A free online course from The University of Edinburgh
• Theory of Inference - Course by Simon Wood
• Teaching Statistics and Data Science Online - Workshop series by Mine Çetinkaya-Rundel and Colin Rundel

• APFr: a multiple testing approach based on Average Power Function and Bayes FDR robust estimation - Nicolò Margaritella
• ASSA: for applied singular spectrum analysis - Miguel de Carvalho and Gabriel Martos
• bestSDP: estimates the burden of common communicable diseases in settlements of displaced populations - You Li
• catmap: a case-control and TDT meta-analysis package - Kristin Nicodemus et. al.
• CPS: sequential and batch change detection for univariate data streams, using the change point model framework - Gordon Ross
• ctmcd: estimates the parameters of a continuous-time Markov chain from discrete-time data - Marius Pfeuffer, Gonçalo dos Reis et al.
• DDEfit: a package for fitting (delay) differential equations and discrete time models to data - Simon Wood
• dirichletprocess: for nonparametric Bayesian analysis using Dirichlet processes - Gordon Ross
• encryptr: encrypt and decrypt data using RSA keys - Ewen Harrison et. al.​​​​​​
• extremis: conducts inferece for statistical models for extreme values - Miguel de Carvalho 
• finalfit: quickly create elegant regression results tables and plots when modelling - Ewen Harrison, Tom Drake & Riinu Ots
• fmesher: a geometry tool in the INLA package - Finn Lindgren
• geometry: for mesh generation and surface tessellation - David C. Sterratt et. al.
• hsstan: hierarchical shrinkage Stan models for biomarker selection - Marco Colombo, Paul McKeigue & Athina Spiliopoulou
• inlabru: for spatial modelling using integrated nested Laplace Approximation - Finn Lindgren
• mgcv: for estimating penalized Generalized Linear models - Simon Wood
• nflows: a normalizing flows pytorch library - Iain Murray
• Orthogonal MCMC: MATLAB code for implementing Orthogonal MCMC methods - Victor Elvira
• posum 2: mortality estimation software based on the population surface method - Simon Wood
• retistruct: a program to reconstruct retinae - David C. Sterratt & Daniel Lyngholm
• rGEDI:  A set of tools for downloading, reading, visualizing and processing NASA's GEDI data - Steven Hancock et. al.
• RImageJROI: reads 'ImageJ' ROI files - David C. Sterratt & Mikko
• ROCnReg: estimates ROC Curve Inference with and without Covariates - Maria Xose Rodriguez-Alvarez & Vanda Inacio
• RPEnsemble: for random projection ensemble classification - Timothy Cannings and Richard Samworth
• RTriangle: a 2D quality mesh generator and Delaunay triangulator - Jonathan Richard Shewchuk, David C. Sterratt & Elias Pipping
• Sequential Monte Carlo: MATLAB code for the sequential Monte Carlo scheme - Victor Elvira
• Solv95: a delay differential equation solver - Simon Wood
• spearmanCL: for conducting jackknife Euclidean / empirical likelihood inference for Spearman's rho - Miguel de Carvalho
• texmex: for statistical extreme value modelling of threshold excesses, maxima and multivariate extremes - Ioannis Papastathopoulos et. al.
• wevid: for quantifying performance of a binary classifier through weight of evidence - Paul McKeigue & Marco Colombo
• wktmo: for converting weekly data to monthly data - You Li

Stats-based animation for teaching - Glenna Nightingale

• ChiSquare: The Chi Square test of independence at the Chocolate factory

• taking_the_biscuit: Data storyboarding with Glenna Nightingale