The article Calculus in R first appeared on DataScience+.
Calculus is a branch of mathematics that involves the study of rates of change. Before calculus was invented, all math was static: It could only help calculate objects that were perfectly still. But the universe is constantly moving and changing. No objects—from the stars in space to subatomic particles or cells in the body—are always at rest. Indeed, just about everything in the universe is constantly moving. Calculus helped to determine how particles, stars, and matter actually move and change in real time.
Calculus is used in a multitude of fields that you wouldn’t ordinarily think would make use of its concepts. Among them are physics, engineering, economics, statistics, and medicine. Calculus is also used in such disparate areas as space travel, as well as determining how medications interact with the body, and even how to build safer structures. You’ll understand why calculus is useful in so many areas if you know a bit about its history as well as what it is designed to do and measure.
Math is one of the key building blocks of data science. If you want to understand what’s going on under the hood in your machine learning work as a data scientist, you’ll need to have a solid grasp of the fundamentals of calculus. While you cannot do a lot of data science with just calculus, the topic is essential for more advanced topics in data science such as machine learning, algorithms, and advanced statistics.
Let’s get started using calculus with R:
Functions in R
Let us first try to do a function and
f <- makeFun(m * x + b ~ x, m = 3.5, b = 10)
f(x = 2)
g <- makeFun(A * x * cos(pi * x * y) ~ x + y, A = 3)
function (x, y, A = 3)
A * x * cos(pi * x * y)
g(x = 1, y = 2)
Let us try plotting the calculus function
plotFun(A * exp(k * t) * sin(2 * pi * t/P) ~ t + k, t.lim = range(0, 10), k.lim = range(-0.3,0), A = 10, P = 4)
Let us try do do another function in R:
plotFun(A * exp(k * t) * sin(2 * pi * t/P) ~ t + k, t.lim = range(0, 10),k.lim = range(-0.3,0), A = 10, P = 4, surface = TRUE)
Let us try do do a third function in R:
plotFun(dt(t, df) ~ t + df, t.lim = range(-3,3), df.lim = range(1,10))
Visit to read the full article and download additional R code:
Disclosure: Interactive Brokers
Information posted on IBKR Traders’ Insight that is provided by third-parties and not by Interactive Brokers does NOT constitute a recommendation by Interactive Brokers that you should contract for the services of that third party. Third-party participants who contribute to IBKR Traders’ Insight are independent of Interactive Brokers and Interactive Brokers does not make any representations or warranties concerning the services offered, their past or future performance, or the accuracy of the information provided by the third party. Past performance is no guarantee of future results.
This material is from DataScience+ and is being posted with permission from DataScience+. The views expressed in this material are solely those of the author and/or DataScience+ and IBKR is not endorsing or recommending any investment or trading discussed in the material. This material is not and should not be construed as an offer to sell or the solicitation of an offer to buy any security. To the extent that this material discusses general market activity, industry or sector trends or other broad based economic or political conditions, it should not be construed as research or investment advice. To the extent that it includes references to specific securities, commodities, currencies, or other instruments, those references do not constitute a recommendation to buy, sell or hold such security. This material does not and is not intended to take into account the particular financial conditions, investment objectives or requirements of individual customers. Before acting on this material, you should consider whether it is suitable for your particular circumstances and, as necessary, seek professional advice.
In accordance with EU regulation: The statements in this document shall not be considered as an objective or independent explanation of the matters. Please note that this document (a) has not been prepared in accordance with legal requirements designed to promote the independence of investment research, and (b) is not subject to any prohibition on dealing ahead of the dissemination or publication of investment research.
Any trading symbols displayed are for illustrative purposes only and are not intended to portray recommendations.