4 docs tagged with "statistics"

Aggregation combines multiple values into a single summary value. Common operations include sum, mean, count, min, max, and custom aggregations.

Boost.Accumulators is a framework for incremental statistical computation. You push data

Boost.Math is a comprehensive mathematics library that goes far beyond what `` provides.

Fitting a model is estimating parameters from a finite sample — and every estimate comes with uncertainty about how wrong it might be. This page derives maximum likelihood estimation, the principle underlying nearly every loss function used in this knowledge base, and shows the bridge from "most likely parameters" to "squared error" and "cross-entropy."