AN INTRODUCTION TO R: SOFTWARE FOR STATISTICAL MODELLING AND COMPUTING

By Q. PAVIO

COLOUR PALETTES MATHEMATICAL EXPRESSIONS MAPS, COASTLINES AND CO-ORDINATE SYSTEMS IMPORTING AND EXPORTING GETTING STUFF IN EDITING DATA IMPORTING BINARY FILES READING IN LARGE DATA FILES GETTING STUFF OUT GETTING OUT GRAPHICS MIXED EFFECTS MODELS: AN INTRODUCTION LINEAR MIXED EFFECTS MODELS GENERALIZED LINEAR MIXED EFFECTS MODELS PROGRAMMING INTRODUCTORY EXAMPLE THE CALL COMPONENT AND UPDATING COMBINING TWO ESTIMATES SOME LESSONS SOME UNDER-USED ARRAY AND OTHER FACILITIES SOME LITTLE-USED DEBUGGING FUNCTIONS AND SUPPORT SYSTEMS COMPILED CODE AND PACKAGES MAKING AND MAINTAINING EXTENSIONS NEURAL NETWORKS: AN INTRODUCTION METHODOLOGY REGRESSION FUNCTION PENALIZED ESTIMATION TREE-BASED MODELS I: CLASSI?CATION TREES DECISION TREE METHODOLOGY RECURSIVE PARTITIONING AND REGRESSION TREES (RPART) A CLASSI?CATION EXAMPLE: FISHER’S IRIS DATA PRUNING TREES PREDICTIONS PLOTTING OPTIONS TREE-BASED MODELS II: REGRESSION TREES AND ADVANCED TOPICS REGRESSION TREES ADVANCED TOPICS