Articles by Kostiantyn Kravchuk

Parallel Computing Exercises: Snowfall (Part-1)

July 6, 2017 | Kostiantyn Kravchuk

R has a lot of tools to speed up computations making use of multiple CPU cores either on one computer, or on multiple machines. This series of exercises aims to introduce the basic techniques for implementing parallel computations using multiple CPU cores on one machine. The initial step in preparation ... [Read more...]

Density-Based Clustering Exercises

June 10, 2017 | Kostiantyn Kravchuk

Density-based clustering is a technique that allows to partition data into groups with similar characteristics (clusters) but does not require specifying the number of those groups in advance. In density-based clustering, clusters are defined as dense regions of data points separated by low-density regions. Density is measured by the number ... [Read more...]

Forecasting: ARIMAX Model Exercises (Part-5)

May 5, 2017 | Kostiantyn Kravchuk

The standard ARIMA (autoregressive integrated moving average) model allows to make forecasts based only on the past values of the forecast variable. The model assumes that future values of a variable linearly depend on its past values, as well as on the values of past (stochastic) shocks. The ARIMAX model ... [Read more...]

Forecasting: Multivariate Regression Exercises (Part-4)

May 1, 2017 | Kostiantyn Kravchuk

In the previous exercises of this series, forecasts were based only on an analysis of the forecast variable. Another approach to forecasting is to use external variables, which serve as predictors. This set of exercises focuses on forecasting with the standard multivariate linear regression. Running regressions may appear straightforward but ... [Read more...]

Correlation and Correlogram Exercises

April 8, 2017 | Kostiantyn Kravchuk

Correlation analysis is one of the most popular techniques for data exploration. This set of exercises is intended to help you to extend, speed up, and validate your correlation analysis. It allows to practice in: – calculating linear and nonlinear correlation coefficients, – testing those coefficients for statistical significance, – creating correlation matrices ... [Read more...]

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