Amanote Research

Amanote Research

  • Register
  • Sign In

Scmamp: Statistical Comparison of Multiple Algorithms in Multiple Problems

R Journal- United States

doi 10.32614/rj-2016-017

Full Text

Abstract

Available in

Categories

UncertaintyNumerical AnalysisStatisticsProbability

Date

January 1, 2016

Authors

Borja CalvoGuzmán Santafé

Publisher

The R Foundation


Related search

Mulcom: A Multiple Comparison Statistical Test for Microarray Data in Bioconductor

BMC Bioinformatics
BiochemistryApplied MathematicsComputer Science ApplicationsStructural BiologyMolecular Biology
2011English

Comparison of Different Analysis Algorithms to Calculate Multiple-Breath Washout Outcomes

ERJ Open Research
PulmonaryRespiratory Medicine
2018English

Multiple‐Chapter Problems

2019English

Absent Multiple Kernel Learning Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern RecognitionApplied MathematicsComputer VisionMathematicsComputational TheoryArtificial IntelligenceSoftware
2019English

Multiple Sources in Statistical Room Acoustics

Journal of the Acoustical Society of America
AcousticsUltrasonicsArtsHumanities
1982English

Statistical Analysis of Noncommensurate Multiple Outcomes

Circulation. Cardiovascular quality and outcomes
MedicineCardiovascular MedicineCardiology
2011English

Multiple Multicast Tree Construction and Multiple Description Video Assignment Algorithms

2011English

Statistical Study of the Multiple Fractures.

Orthopedics & Traumatology
1987English

Multiple Comparison Procedures /

1965English

Amanote Research

Note-taking for researchers

Follow Amanote


© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy