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
|