# Fast implementation of the Smallest Maximizer Criterion for unbounded context tree model selection

> document published in 2014

**Wikidata**: [Q102054471](https://www.wikidata.org/wiki/Q102054471)  
**Source**: https://4ort.xyz/entity/fast-implementation-of-the-smallest-maximizer-criterion-for-unbounded-context-tree-model-selection

## Summary

Fast implementation of the Smallest Maximizer Criterion for unbounded context tree model selection is a document[1].

## Summary
Fast implementation of the Smallest Maximizer Criterion for unbounded context tree model selection is a document published in 2014. It is a scholarly work authored by researchers affiliated with the NeuroMat institute, presenting an algorithm for statistical model selection.

## Key Facts
- **Title:** Fast implementation of the Smallest Maximizer Criterion for unbounded context tree model selection.
- **Publication Date:** September 30, 2014.
- **Instance Of:** Document (a form for the preservation of structured and identified information).
- **Authors:** Antonio Galves (sequence position 3), Aldana M González Montoro (sequence position 1), and Arnaldo Mandel (sequence position 2).
- **Language:** English.
- **Part Of:** NeuroMat research institute, with the project supported by the São Paulo Research Foundation (FAPESP grant 2013/07699-0).
- **Published In:** NeuroMat Institutional Repository.
- **Work Available At:** https://scholar.google.com/scholar?cluster=15444217231678620779&hl=en&oi=scholarr
- **Wikidata Description:** Document published in 2014.

## FAQs
**Who are the authors of this document?**
The document has three authors: Aldana M González Montoro is listed as the first author, Arnaldo Mandel as the second, and Antonio Galves, the director of the NeuroMat institute, as the third.

**What institution is associated with this research?**
The work is part of the NeuroMat research institute, which is funded by the São Paulo Research Foundation (FAPESP). NeuroMat, founded in 2013 and based in São Paulo, Brazil, specializes in neuromathematics.

**What type of publication is this?**
It is formally classified as a document, which is an information resource defined by its structure, comprising document-type information, communications media, and a heading. It is archived in the NeuroMat Institutional Repository.

## Why It Matters
This document represents a contribution to the field of statistical model selection, specifically for unbounded context tree models. Its development within the NeuroMat institute highlights the application of advanced mathematical techniques to complex problems, a core mission of the center. By making the algorithm's implementation publicly available, it facilitates further research and application in areas requiring sophisticated model selection, potentially impacting fields that rely on statistical inference and data analysis.

## Notable For
- **Affiliation:** Being a product of the NeuroMat research institute, a center dedicated to pioneering work in neuromathematics.
- **Authorship:** Featuring Antonio Galves, the director of NeuroMat, as a co-author.
- **Structural Classification:** It is a defined instance of a "document," a key concept in information science with a specific ontological structure.

## Body

### Document Classification and Structure
This entity is an instance of a **document**, which is formally defined as a form for the preservation of structured and identified information. As an information resource, it is structurally composed of specific elements: **document-type information**, **communications media**, and a **heading**. This classification distinguishes it from a generic record and places it within a framework studied by **library science**.

### Authors and Affiliation
The document has three authors, listed with explicit sequence numbers:
*   **Aldana M González Montoro** is the first author (sequence position 1).
*   **Arnaldo Mandel** is the second author (sequence position 2).
*   **Antonio Galves** is the third author (sequence position 3). Antonio Galves is also the director of the NeuroMat institute.

The work is a part of **NeuroMat**, a research institute founded in 2013 with a focus on neuromathematics. The project is specifically linked to the São Paulo Research Foundation via grant **FAPESP 2013/07699-0**. NeuroMat is headquartered in the Antonio Galves building in São Paulo, Brazil.

### Publication Details
The document was published on **September 30, 2014**. It is written in **English** and was published in the **NeuroMat Institutional Repository**. The primary access point for the work is a Google Scholar link: `https://scholar.google.com/scholar?cluster=15444217231678620779&hl=en&oi=scholarr`.

### Context within Information Science
As a document, the entity falls under the **Dewey Decimal Classification** **025.1714**. The concept of a document is recognized globally by authority systems such as the **GND ID** (4180009-6), the **UNESCO Thesaurus** (concept502), and the **Great Russian Encyclopedia Portal**. In the semantic web, a document is an equivalent class to `https://www.w3.org/ns/activitystreams#Document`.

## References

1. [Source](https://scholar.google.com/scholar?cluster=15444217231678620779&hl=en&oi=scholarr)