Understanding Predictive Models Using R Software

Analysing data and using it to predict future events has become an extremely important aspect in this era when data is so rapidly generated everywhere. For this purpose, many traditional and data driven predictive models are available in statistical literature. For a new researcher or data analyst, the choice of a regression model for a particular situation is very difficult as there are plenty of predictive models available for data analysis for different situations. This book will help the researcher understand the different predictive models. It gives a glimpse of many traditional as well as data driven models available for different situations. It also describes those models from a statistical point of view with illustrations using R software for better understanding. It also provides the comparison between the models to have a clear idea about the different assumptions on which the models are based, and the solution if any assumption is violated. The book also mentions the different situations that researchers have to tackle while fitting models like dealing with outliers, overfitting, and heterogeneity in the data.