By S. K. Regonda, B. Rajagopalan, U. Lall, M. Clark, and Y.-I. Moon. Published in Nonlinear Processes in Geophysics (Part of Special Issue “Nonlinear deterministic dynamics in hydrologic systems: ...

Polynomial regression model for a single predictor, X, is: where h is called the degree of the polynomial. For lower degrees, the relationship has a specific name (i.e., h = 2 is called quadratic, h = ...

The causality analysis of multivariate time series and formation of complex networks relies on the estimation of the direct cause-effect from one observed variable to another accounting for the ...

Time series uses methods such as smoothing, decomposition, autocorrelation, and ARIMA models, while regression uses methods such as linear, logistic, polynomial, and multivariate models.

This project utilizes time series analysis and machine learning models to predict housing prices (ZHVI) and rent prices (ZORI) for various regions. The project implements SARIMA and ARIMA models for ...

Understanding of Non-Linear Regression Models; Knowledge of programming ; Polynomial Regression. Polynomial regression is very similar to linear regression but additionally, it considers polynomial ...

Regonda, S., B. Rajagopalan, U. Lall, M. Clark and Y. Moon, Local polynomial mehtod for ensemble forecast of time series, Nonlinear Processes in Geophysics, Special issue on "Nonlinear Deterministic ...

The causality analysis of multivariate time series and formation of complex networks relies on the estimation of the direct cause-effect from one observed variable to another accounting for the ...