Prediction of future observations using belief functions: A likelihood-based approach

Prediction of future observations using belief functions: A likelihood-based approach

© 2015 Elsevier Inc. All rights reserved. We study a new approach to statistical prediction in the Dempster-Shafer framework. Given a parametric model, the random variable to be predicted is expressed as a function of the parameter and a pivotal random variable. A consonant belief function in the pa...

Saved in:

書目詳細資料
Main Authors:	Kanjanatarakul O., Denœux T., Sriboonchitta S.
格式:	雜誌
出版:	2017
在線閱讀:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84962822288&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/41915
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

相似書籍

Prediction of future observations using belief functions: A likelihood-based approach
由: Orakanya Kanjanatarakul, et al.
出版: (2018)

Estimation and prediction using belief functions: Application to stochastic frontier analysis
由: Kanjanatarakul,O., et al.
出版: (2015)

Forecasting using belief functions: An application to marketing econometrics
由: Kanjanatarakul O., et al.
出版: (2014)

K-EVCLUS: Clustering large dissimilarity data in the belief function framework
由: Kanjanatarakul O., et al.
出版: (2017)

Forecasting using belief functions: An application to marketing econometrics
由: Orakanya Kanjanatarakul, et al.
出版: (2018)

Forecasting using belief functions: An application to marketing econometrics
由: Orakanya Kanjanatarakul, et al.
出版: (2018)

K-EVCLUS: Clustering large dissimilarity data in the belief function framework
由: Orakanya Kanjanatarakul, et al.
出版: (2018)

Comparing linear and nonlinear models in forecasting telephone subscriptions using likelihood based belief functions
由: Noppasit Chakpitak, et al.
出版: (2018)

Comparing linear and nonlinear models in forecasting telephone subscriptions using likelihood based belief functions
由: Noppasit Chakpitak, et al.
出版: (2018)

Predicting stock returns in the capital asset pricing model using quantile regression and belief functions
由: Kittawit Autchariyapanitkul, et al.
出版: (2018)

Predicting stock returns in the capital asset pricing model using quantile regression and belief functions
由: Kittawit Autchariyapanitkul, et al.
出版: (2018)

Econometric forecasting using linear regression and belief functions
由: Orakanya Kanjanatarakul, et al.
出版: (2018)

Econometric forecasting using linear regression and belief functions
由: Orakanya Kanjanatarakul, et al.
出版: (2018)

Evidential clustering of large dissimilarity data
由: Denœux T., et al.
出版: (2017)

EK-NNclus: A clustering procedure based on the evidential K-nearest neighbor rule
由: Thierry Denœux, et al.
出版: (2018)

EK-NNclus: A clustering procedure based on the evidential K-nearest neighbor rule
由: Thierry Denœux, et al.
出版: (2018)

A new evidential K-nearest neighbor rule based on contextual discounting with partially supervised learning
由: Thierry Denœux, et al.
出版: (2020)

Forecasting Using Information and Entropy Based on Belief Functions
由: Woraphon Yamaka, et al.
出版: (2020)

Predictive recursion maximum likelihood of threshold autoregressive model
由: Pastpipatkul P., et al.
出版: (2017)

Reliability prediction through degradation data modeling using a quasi-likelihood approach
由: Jayaram, J.S.R., et al.
出版: (2014)

Predictive recursion maximum likelihood of threshold autoregressive model
由: Pathairat Pastpipatkul, et al.
出版: (2018)

Predictive recursion maximum likelihood of threshold autoregressive model
由: Pathairat Pastpipatkul, et al.
出版: (2018)

The likelihood of present and future bank switching.
由: Ng Elaine, Tan Lee Huang, Ong Wee Hong
出版: (2014)

Empirical likelihood-based confidence intervals for data with possible zero observations
由: Chen, S.X., et al.
出版: (2014)

Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory
由: Denoeux T., et al.
出版: (2017)

Forecasting tourist arrivals to Thailand using belief functions
由: Min,N., et al.
出版: (2015)

Evidential clustering of large dissimilarity data
由: Thierry Denœux, et al.
出版: (2018)

Time series forecast using AR-belief approach
由: Thianpaen N., et al.
出版: (2017)

Time series forecast using AR-belief approach
由: Nantiworn Thianpaen, et al.
出版: (2018)

Estimating oil price value at risk using belief functions
由: Phochanachan,P., et al.
出版: (2015)

Maximum likelihood estimation of partially observed diffusion models
由: KLEPPE, Tore Selland, et al.
出版: (2014)

The interactive effect of insight and cuteness in driving purchase likelihood: a lay belief of creativity
由: Septianto, Felix, et al.
出版: (2022)

Forecasting risk and returns: CAPM model with belief functions
由: Sutthiporn Piamsuwannakit, et al.
出版: (2018)

Forecasting risk and returns: CAPM model with belief functions
由: Sutthiporn Piamsuwannakit, et al.
出版: (2018)

Log-likelihood metrics based on two-symbol-interval observations for LDPC codes with BDPSK transmission
由: Mo, E., et al.
出版: (2014)

Forecasting inbound tourism demand to China using time series models and belief functions
由: Jiechen Tang, et al.
出版: (2018)

Forecasting inbound tourism demand to China using time series models and belief functions
由: Jiechen Tang, et al.
出版: (2018)

Evaluating and Comparing Soft Partitions: an Approach Based on Dempster-Shafer Theory
由: Thierry Denoeux, et al.
出版: (2018)

Non-likelihood estimation methods for spatial predictions
由: Heng, Chloe Yi Ning
出版: (2024)

Genetic Neural Network for Diabetes Likelihood Prediction Using Risk Factors
由: Gamara, Rex Paolo C, et al.
出版: (2023)