In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

For time-series analysis, it is possible to develop a linear regression model that simply fits a line to the variable's historical performance and extrapolates that into the future.

Zheng Yuan, Yuhong Yang, Combining Linear Regression Models: When and How?, Journal of the American Statistical Association, Vol. 100, No. 472 (Dec., 2005), pp. 1202-1214 ...

Learn what heteroscedasticity means, its types, and how it affects financial models. Understand the intricacies of volatility ...

Before building my model, I want to step back to offer an easy-to-understand definition of linear regression and why it’s vital to analyzing data. What is linear regression?

Course Topics Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous ...

Learn how ARIMA models use time series data for accurate short-term forecasting. Discover its pros, cons, and essential tips ...