June 2019
Beginner to intermediate
598 pages
12h 10m
English
Content preview from R Cookbook, 2nd Edition
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Chapter 13. Beyond Basic Numerics and Statistics
This chapter presents a few advanced techniques such as those you might encounter in the first or second year of a graduate program in applied statistics.
Most of these recipes use functions available in the base distribution. Through add-on packages, R provides some of the world’s most advanced statistical techniques. This is because researchers in statistics now use R as their lingua franca, showcasing their newest work. Anyone looking for a cutting-edge statistical technique is urged to search CRAN and the web for possible implementations.
13.1 Minimizing or Maximizing a Single-Parameter Function
Problem
Given a single-parameter function f, you want to find the point at
which f reaches its minimum or maximum.
Solution
To minimize a single-parameter function, use optimize. Specify the
function to be minimized and the bounds for its domain (x):
optimize(f,lower=lowerBound,upper=upperBound)
If you instead want to maximize the function, specify maximum = TRUE:
optimize(f,lower=lowerBound,upper=upperBound,maximum=TRUE)
Discussion
The optimize function can handle functions of one argument. It
requires upper and lower bounds for x that delimit the region to be
searched. The following example finds the minimum of a polynomial,
3x4 – 2x3 + 3x2 – 4x + 5:
f<-function(x)3*x^4-2*x^3+3*x^2-4*x+5optimize(f,lower=-20,upper=20)#> $minimum#> [1] 0.597#>#> $objective#> [1] 3.64
The returned ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.