Identifying Complex Causal Dependencies in Configurational Data with Coincidence Analysis
We present cna, a package for performing Coincidence Analysis (CNA). CNA is a configurational comparative method for the identification of complex causal dependencies—in particular, causal chains and common cause structures—in configurational data. After a brief introduction to the method’s theoretical background and main algorithmic ideas, we demonstrate the use of the package by means of an artificial and a real-life data set. Moreover, we outline planned enhancements of the package that will further increase its applicability.

Autoregressive Conditional Poisson Model – I
Modeling the time series of count outcome is of interest in the operational risk while forecasting the frequency of losses. Below is an example showing how to estimate a simple ACP(1, 1) model, e.g. Autoregressive Conditional Poisson, without covariates with ACP package.

Visualizing the causes of airline crashes
There has been a spate of recent high-profile airline crashes (Malaysia Airlines, TransAsia Airways, Germanwings,…) so I was surprised when I saw a time series plot of the number of airline crashes by year, which indicates that the annual number of airline crashes has been decreasing since 1993. The data show that the annual number of crashes in recent years is about half of the number from 20 years ago.

Big Data Certifications: Finding The One That Works For You
We can’t tell you which big data certification programs to choose – that depends on a number of variables in your personal IT career goals and work situation. What we can do is provide you with a selected list of the vendor certifications available.

Using Apache Spark in the Enterprise
The industry intensity around Apache Spark, an in-memory processing framework widely believed to succeed MapReduce, has captured the market’s imagination for its impressive data exploration engine. Spark gives data scientists and analysts a rich language to explore data rapidly, iteratively and with a suite of timesaving and advanced function libraries.

Text Analytics 2015 – Technology and Market Overview
A leading analyst and expert on text analytics gives an overview of the past year and looks ahead on text analytics technology and market developments