AI and Machine Learning

Regression Analysis

Regression analysis is used for predicting forecasting with substantial overlap in relation to respective environments. It can be used to decipher the causal relationship between the independent and dependent variables. The application domain includes practically anything and everything starting from business predictions to computational domain to scientific research. Regression involving correlated responses (time series and growth curves); regression in which the response variations are curves, images, multi-dimensional profiles and other complex data objects; methods accommodating missing data, non-parametric and Bayesian methods etc. maybe referred to as upcoming topics in the field of regression analysis research. Variety of a commercial software packages are available for performing regression analysis. Majority of the packages works on the principle of least square error. However many other packages are available that can perform various non-parametric and robust regression specialized software has also been developed for survey analysis.