Statistical Modeling

ARIMA Model is a statistical method used for time series forecasting, combining autoregression, integration, and moving averages.

An autoregressive model predicts future values based on past values in a time series.

Curve fitting is a statistical technique used to find a curve that best represents a dataset.

Gradient Boosting is a machine learning technique that builds models sequentially to improve prediction accuracy.

The Laplace distribution is a probability distribution with a peaked shape, used in statistics and machine learning.

A statistical model combining multiple softmax functions to represent complex distributions.

Non-linear regression models relationships that aren't straight lines, capturing complex patterns in data.

Ordinal regression is a statistical method used to predict ordered outcomes.

Parametric regression is a statistical method that models relationships using predefined equations with parameters.