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An improved method for forecasting spare parts demand using extreme value theory
16 references·6 citing·30 second hop
An improved method for forecasting spare parts demand using extreme value theory (2017)An improved method for forecasting spare …Extreme Value Theory: An Introduction (2007)Extreme Value Theory: An Intr…Winning in the aftermarket (2006)Winning in the aftermarketExtreme value theory : an introduction (2006)Extreme value theory : an int…The accuracy of intermittent demand estimates (2004)The accuracy of intermittent …Statistics of Extremes: Theory and Applications (2004)Statistics of Extremes: Theor…Statistics of Extremes (2004)Statistics of ExtremesA new approach to forecasting intermittent demand for service parts inventories (2003)A new approach to forecasting…MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS (2002)MIXING AND MOMENT PROPERTIES …An overview of recent literature on spare parts inventories (2002)An overview of recent literat…An Introduction to Statistical Modeling of Extreme Values (2002)An Introduction to Statistica…Using a Bootstrap Method to Choose the Sample Fraction in Tail Index Estimation (2001)Using a Bootstrap Method to C…Statistical Analysis of Extreme Values: with Applications to Insurance, Finance, Hydrology and Other Fields (2001)Statistical Analysis of Extre…An Introduction to Statistical Modeling of Extreme Values (2001)An Introduction to Statistica…A Moment Estimator for the Index of an Extreme-Value Distribution (1989)A Moment Estimator for the In…Residual Life Time at Great Age (1974)Residual Life Time at Great A…Forecasting and Stock Control for Intermittent Demands (1972)Forecasting and Stock Control…A novel multi-phase hierarchical forecasting approach with machine learning in supply chain management (2023)A novel multi-phase hierarchi…Intermittent demand forecasting for spare parts: A Critical review (2021)Intermittent demand forecasti…Demand forecasting in supply chains: a review of aggregation and hierarchical approaches (2021)Demand forecasting in supply …Inventory Management Model Based on Lean Supply Chain to Increase the Service Level in a Distributor of Automotive Sector (2020)Inventory Management Model Ba…Integrating ABC analysis and rough set theory to control the inventories of distributor in the supply chain of auto spare parts (2019)Integrating ABC analysis and …Classification methodology for spare parts management combining maintenance and logistics perspectives (2018)Classification methodology fo…Time Series Analysis: Forecasting and Control (1977)25 years of time series forecasting (2006)Automatic Time Series Forecasting: The forecast Package for R (2008)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Estimation of multivariate models for time series of possibly different lengths (2006)Copula–Based Models for Financial Time Series (2009)Modelling Nonlinear Economic Time Series (2010)Idea Generation and the Quality of the Best Idea (2010)Quantitative Risk Management (2011)Top Incomes in the Long Run of History (2011)Statistical Modeling of Spatial Extremes (2012)Tail Risk and Asset Prices (2014)Understanding Heterogeneity in Clinical Cohorts Using Normative Models: Beyond Case-Control Studies (2016)Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory (1997)Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach (2000)Extreme Correlation of International Equity Markets (2001)Extreme events: dynamics, statistics and prediction (2011)Extremal t processes: Elliptical domain of attraction and a spectral representation (2013)On the block maxima method in extreme value theory: PWM estimators (2014)Heavy tail modeling and teletraffic data: special invited paper (1997)Tail Index Estimation and an Exponential Regression Model (1999)A Conditional Approach for Multivariate Extreme Values (with Discussion) (2004)Stationary max-stable fields associated to negative definite functions (2009)Power-law distributions in empirical data (2018)Power Laws in Economics and Finance (2009)A multivariate copula‐based framework for dealing with hazard scenarios and failure probabilities (2016)Value-at-risk versus expected shortfall: A practical perspective (2004)
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References

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  • 2002MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS566 cited
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  • 2002An overview of recent literature on spare parts inventories504 cited
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  • 2006Winning in the aftermarket462 cited
  • 2001Using a Bootstrap Method to Choose the Sample Fraction in Tail Index Estimation452 cited
  • 2001Statistical Analysis of Extreme Values: with Applications to Insurance, Finance, Hydrology and Other Fields422 cited
  • 2003A new approach to forecasting intermittent demand for service parts inventories

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395 cited

Cited by

  • 2021Intermittent demand forecasting for spare parts: A Critical review89 cited
  • 2021Demand forecasting in supply chains: a review of aggregation and hierarchical approaches87 cited
  • 2019Integrating ABC analysis and rough set theory to control the inventories of distributor in the supply chain of auto spare parts50 cited
  • 2018Classification methodology for spare parts management combining maintenance and logistics perspectives49 cited
  • 2023A novel multi-phase hierarchical forecasting approach with machine learning in supply chain management37 cited
  • 2020Inventory Management Model Based on Lean Supply Chain to Increase the Service Level in a Distributor of Automotive Sector18 cited