Optimizing R Code with Rcpp
Use C++ to dramatically boost the performance of your R code.Start Course for Free
4 Hours15 Videos52 Exercises3,154 Learners4350 XP
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R is a great language for data science, but sometimes the code can be slow to run. Combining the comfort of R with the speed of a compiled language is a great way to reclaim the performance your code deserves. C++ is a modern, high performance language that is simple enough to learn in the context of accelerating R code. With the help of the Rcpp package, C++ integrates very neatly with R. You will learn how to create and manipulate typical R objects (vectors and lists), and write your own C++ functions to dramatically boost the performance of your R code.
Writing, benchmarking, and debugging your first C++ code.
Functions and Control Flow
Writing functions, controlling the flow with if and else, and learning to use the three kinds of loops in C++.C++ functions belong to C++ files50 xpWhat happens when you compile this C++ file50 xpBoiler plate100 xpWriting functions in C++50 xpFirst function - again100 xpExported and unexported functions100 xpR code in C++ files100 xpif and if/else100 xpFor loops50 xpCalculating square roots with a for loop100 xpBreaking out of a for loop100 xpWhile loops50 xpCalculating square roots with a while loop100 xpDo it again: do-while loop100 xp
Manipulate and compute with Rcpp and native C++ vectors.Rcpp classes and vectors50 xpFirst and last values of a vector50 xpIndexing a vector100 xpSum of double vector100 xpCreating vectors50 xpSequence of integers100 xpCreate vector with given values100 xpVector cloning100 xpWeighted mean50 xpWeighted mean (C++ version)100 xpHandling of missing values100 xpVectors from the STL50 xpDon't change the size of Rcpp vectors100 xpSTL vectors100 xp
Use random numbers and write algorithms for applied time series models.Random number generation50 xpScalar random number generation100 xpSampling from a mixture of distributions (I)100 xpSampling from a mixture of distributions (II)100 xpRolling operations50 xpRolling means100 xpRolling means (in C++)100 xpLast observation carried forward100 xpMean carried forward100 xpAuto regressive model50 xpSimulate AR(p) model100 xpSimulate MA(q) model100 xpARMA (p, q) model100 xpCongratulations!50 xp
PrerequisitesIntroduction to Writing Functions in R
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