دانلود کتاب Functional Programming in R 4: Advanced Statistical Programming for Data Science, Analysis, and Finance

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Table of Contents\nAbout the Author\nAbout the Technical Reviewer\nAcknowledgments\nChapter 1: Introduction\nChapter 2: Functions in R\n Writing Functions in R\n Named Parameters and Default Parameters\n The “Gobble Up Everything Else” Parameter: “...”\n Lazy Evaluation\n Functions Don’t Have Names\n Vectorized Functions\n Infix Operators\n Replacement Functions\nUntitled\nChapter 3: Pure Functional Programming\n Writing Pure Functions\n Recursion As Loops\n The Structure of a Recursive Function\n Tail-Recursion\n Runtime Considerations\nChapter 4: Scope and Closures\n Environments and Functions\n Environment Chains, Scope, and Function Calls\n Scopes, Lazy Evaluation, and Default Parameters\n Nested Functions and Scopes\n Closures\n Reaching Outside Your Innermost Scope\n Lexical and Dynamic Scope\nChapter 5: Higher-Order Functions\n Currying\n A Parameter Binding Function\n Continuation-Passing Style\n Thunks and Trampolines\nChapter 6: Filter, Map, and Reduce\n The General Sequence Object in R Is a List\n Filtering Sequences\n Mapping over Sequences\n Reducing Sequences\n Bringing the Functions Together\n The Apply Family of Functions\n sapply, vapply, and lapply\n The apply Function\n The tapply Function\n Functional Programming in purrr\n Filter-like Functions\n Map-like Functions\n Reduce-like Functions\nChapter 7: Point-Free Programming\n Function Composition\n Pipelines\nChapter 8: Conclusions\nIndex