Tag Archives: R programming courses in Pune

Analyze Smartphone Sensor Data with R and the BreakoutDetection Package

Analyze-Smartphone-Sensor-Data-with-R-and-the-BreakoutDetection-Package
 

Quite interetsing. Juggling with sensor data is starkly different from economics data, document processing or social networking, but very worthwhile. In this blog, we will take a practical approach to analyze smartphone sensor data with R. We are going to use the accelerometer smartphone data that Datarella presented in its Data Fiction competition. The dataset signifies the stimulation along the three axes of the smartphone:

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How to Create Repeat Loop in R Programming

In this tutorial, we will learn to make a repeat loop with the use of R programming.
 
How to Create Repeat Loop in R Programming
 
A repeat loop is used to iterate over a block of code over several number of times.

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Debugging Magrittr Pipelines in R with Bizarro Pipe and Eager Assignment

Debugging Magrittr Pipelines in R with Bizarro Pipe and Eager Assignment

 

Pipes in R

Pipe, written as “%>%“ is basically an efficient operator, supplied by magrittr R package. The pipe operator is notably famous due to its wide range of use in dplyr and by the proficient dplyr users. The usage of pipe operator allows one to write “sin(5)” as “5 %>% sin“,  which is inspired by F#‘s pipe-forward operator “|>” and is further characterised by:

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How To Visualize Multivariate Relationships in Large Datasets in R Programming:

How To Visualize Multivariate Relationships in Large Datasets in R Programming:
 

In this post, we will discuss how to use the package nmle in R programming, which includes the dataset MathArchieve. To install the package and load it into your R programming environment, use the code mentioned below:

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ANZ uses R programming for Credit Risk Analysis

At the previous month’s “R user group meeting in Melbourne”, they had a theme going; which was “Experiences with using SAS and R in insurance and banking”. In that convention, Hong Ooi from ANZ (Australia and New Zealand Banking Group) spoke on the “experiences in credit risk analysis with R”. He gave a presentation, which has a great story told through slides about implementing R programming for fiscal analyses at a few major banks.

 
ANZ uses R programming for Credit Risk Analysis
 

In the slides he made, one can see the following:

 

How R is used to fit models for mortgage loss at ANZ

A customized model is made to assess the probability of default for individual’s loans with a heavy tailed T distribution for volatility.

One slide goes on to display how the standard lm function for regression is adapted for a non-Gaussian error distribution — one of the many benefits of having the source code available in R.

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