Implementing Monte Carlo Method in R
Implementing Monte Carlo Method in R
Duration: 1h 42m 40s | .MP4 1920x1080, 30 fps(r) | AAC, 48000 Hz, 2ch | 178 MB
Genre: eLearning | Language: English
Duration: 1h 42m 40s | .MP4 1920x1080, 30 fps(r) | AAC, 48000 Hz, 2ch | 178 MB
Genre: eLearning | Language: English
Some problems are difficult or impossible to solve with standard mathematical or statistical approaches - these can often be solved by using the Monte Carlo method. This course covers multiple Monte Carlo applications for ready use.
What you'll learn
Repeated sampling using the Monte Carlo method can be a much more efficient approach in solving difficult problems vs. standard mathematical or statistical practices. In this course, Implementing Monte Carlo Method in R, you’ll gain the ability to build your own Monte Carlo simulations using a variety of approaches and know which solution is most effective. First, you’ll explore the basics behind Monte Carlo and the fundamental functions in R. Next, you’ll discover some simple methods, followed by simulations on stock and commodities data for estimating return probabilities. Finally, you’ll learn how to use Monte Carlo methods on A/B tests. When you’re finished with this course, you’ll have the skills and knowledge of Monte Carlo methods needed to implement these methods yourself.
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