M3 Competition model

GPTKB entity

Statements (61)
Predicate Object
gptkbp:instanceOf statistical model
gptkbp:aimsTo improve forecasting accuracy
gptkbp:designedFor forecasting
gptkbp:developedBy gptkb:M3_Competition
gptkbp:encourages methodological advancements
gptkbp:focusesOn economic forecasting
business forecasting
environmental forecasting
demographic forecasting
gptkbp:hasInventor business strategy
policy making
financial forecasting
resource allocation
supply chain management
https://www.w3.org/2000/01/rdf-schema#label M3 Competition model
gptkbp:includes various forecasting techniques
gptkbp:influencedBy previous forecasting competitions
gptkbp:is_evaluated_by accuracy
gptkbp:isAssociatedWith data analysis
quantitative research
statistical analysis
forecasting competitions
gptkbp:isChallengedBy new forecasting approaches
gptkbp:isCitedIn industry reports
academic papers
gptkbp:isDocumentedIn forecasting textbooks
gptkbp:isEvaluatedBy expert panels
peer review process
user feedback
cross-validation
backtesting
forecasting accuracy metrics
holdout samples
gptkbp:isInfluencedBy historical forecasting methods
gptkbp:isPartOf forecasting literature
gptkbp:isPromotedBy workshops
academic institutions
seminars
industry conferences
forecasting organizations
gptkbp:isPublishedIn gptkb:International_Journal_of_Forecasting
gptkbp:isRecognizedBy forecasting community
gptkbp:isSupportedBy government initiatives
research funding
software tools
collaborative projects
private sector investments
gptkbp:isUsedIn academic research
industry applications
gptkbp:participants practitioners
academic researchers
gptkbp:promotes collaboration between fields
gptkbp:provides benchmark results
gptkbp:relatedTo other forecasting methods
gptkbp:uses time series data
gptkbp:utilizes machine learning techniques
neural networks
regression analysis
exponential smoothing
ARIMA models
gptkbp:yearEstablished 2000