COPULA BASED PREDICTION MODEL

Pearson's correlation coefficient is a measure of association which widely used in many fields. However, Pearson's correlation coefficient has limitation to detect non-linear association. Kendall's Tau and Spearman's Rho are measures of association which can detect both linear an...

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Main Author: (NIM : 10108090); Pembimbing : Khreshna I.A. Syuhada, M.Sc, Ph.D, OCTAVINA
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/16770
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:16770
spelling id-itb.:167702017-09-27T11:42:59ZCOPULA BASED PREDICTION MODEL (NIM : 10108090); Pembimbing : Khreshna I.A. Syuhada, M.Sc, Ph.D, OCTAVINA Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/16770 Pearson's correlation coefficient is a measure of association which widely used in many fields. However, Pearson's correlation coefficient has limitation to detect non-linear association. Kendall's Tau and Spearman's Rho are measures of association which can detect both linear and non-linear association and can be stated in a multivariate distribution function model, named copula. A prediction model is established to predict a value for future observation. Generally, the model prediction is based on Pearson's correlation coefficient. However, considering the limitation that Pearson's correlation coefficient has, in this final project will be established a prediction model based on copula. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Pearson's correlation coefficient is a measure of association which widely used in many fields. However, Pearson's correlation coefficient has limitation to detect non-linear association. Kendall's Tau and Spearman's Rho are measures of association which can detect both linear and non-linear association and can be stated in a multivariate distribution function model, named copula. A prediction model is established to predict a value for future observation. Generally, the model prediction is based on Pearson's correlation coefficient. However, considering the limitation that Pearson's correlation coefficient has, in this final project will be established a prediction model based on copula.
format Final Project
author (NIM : 10108090); Pembimbing : Khreshna I.A. Syuhada, M.Sc, Ph.D, OCTAVINA
spellingShingle (NIM : 10108090); Pembimbing : Khreshna I.A. Syuhada, M.Sc, Ph.D, OCTAVINA
COPULA BASED PREDICTION MODEL
author_facet (NIM : 10108090); Pembimbing : Khreshna I.A. Syuhada, M.Sc, Ph.D, OCTAVINA
author_sort (NIM : 10108090); Pembimbing : Khreshna I.A. Syuhada, M.Sc, Ph.D, OCTAVINA
title COPULA BASED PREDICTION MODEL
title_short COPULA BASED PREDICTION MODEL
title_full COPULA BASED PREDICTION MODEL
title_fullStr COPULA BASED PREDICTION MODEL
title_full_unstemmed COPULA BASED PREDICTION MODEL
title_sort copula based prediction model
url https://digilib.itb.ac.id/gdl/view/16770
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