Submit Search
Upload
Abstract trisnawati
•
0 likes
•
152 views
E
ekaputragunartha
Follow
multivariate analysis/ARIMA/Bootstrap
Read less
Read more
Education
Report
Share
Report
Share
1 of 1
Download now
Download to read offline
Recommended
Parameter-free Modelling of 2D Shapes with Ellipses
Parameter-free Modelling of 2D Shapes with Ellipses
Costas Panagiotakis
Da35573574
Da35573574
IJERA Editor
Economic dispatch using fuzzy logic
Economic dispatch using fuzzy logic
Senthil Kumar
NUMERICAL METHODS
NUMERICAL METHODS
AMOGHA A K
Object Tracking By Online Discriminative Feature Selection Algorithm
Object Tracking By Online Discriminative Feature Selection Algorithm
IRJET Journal
Functional Data Analysis
Functional Data Analysis
COSTARCH Analytical Consulting (P) Ltd.
An integrated framework for 3 d modeling, object detection, and pose estimati...
An integrated framework for 3 d modeling, object detection, and pose estimati...
I3E Technologies
Introduction to Applied Machine Learning
Introduction to Applied Machine Learning
Alireza Doustmohammadi
Recommended
Parameter-free Modelling of 2D Shapes with Ellipses
Parameter-free Modelling of 2D Shapes with Ellipses
Costas Panagiotakis
Da35573574
Da35573574
IJERA Editor
Economic dispatch using fuzzy logic
Economic dispatch using fuzzy logic
Senthil Kumar
NUMERICAL METHODS
NUMERICAL METHODS
AMOGHA A K
Object Tracking By Online Discriminative Feature Selection Algorithm
Object Tracking By Online Discriminative Feature Selection Algorithm
IRJET Journal
Functional Data Analysis
Functional Data Analysis
COSTARCH Analytical Consulting (P) Ltd.
An integrated framework for 3 d modeling, object detection, and pose estimati...
An integrated framework for 3 d modeling, object detection, and pose estimati...
I3E Technologies
Introduction to Applied Machine Learning
Introduction to Applied Machine Learning
Alireza Doustmohammadi
P1161208119
P1161208119
Ashraf Aboshosha
Xmr im
Xmr im
Alkis Vazacopoulos
Operational Research
Operational Research
Roy Thomas
Evaluating & Monitoring Your Process Using MSA & SPC
Evaluating & Monitoring Your Process Using MSA & SPC
JMP software from SAS
Car insurance - data visualization
Car insurance - data visualization
Saleesh Satheeshchandran
Efficient Top-N Recommendation for Very Large Scale Binary Rated Datasets
Efficient Top-N Recommendation for Very Large Scale Binary Rated Datasets
Fabio Aiolli
Monte Carlo Simulation Of Heston Model In Matlab(1)
Monte Carlo Simulation Of Heston Model In Matlab(1)
Amir Kheirollah
Confi.pt_LeanProject_MarketAnalysis
Confi.pt_LeanProject_MarketAnalysis
Mariana Taylor de Jesus
обо мне
обо мне
tatsorokina1
Propuesta sobre educaciã“n seguridad vial y participaciã“n comunitaria en la ...
Propuesta sobre educaciã“n seguridad vial y participaciã“n comunitaria en la ...
proyectosdecorazon
Ídolos de la Juventud
Ídolos de la Juventud
angelkuki
Homework 01
Homework 01
MyongJung Kim
A un año de tu partida
A un año de tu partida
UTH
Pasatiempo
Pasatiempo
Caah1967
Viaje de estudios
Viaje de estudios
romariorivera
We're together
We're together
Farizat Torogeldievna
Performance improvement of a Rainfall Prediction Model using Particle Swarm O...
Performance improvement of a Rainfall Prediction Model using Particle Swarm O...
ijceronline
THE APPLICATION OF BAYES YING-YANG HARMONY BASED GMMS IN ON-LINE SIGNATURE VE...
THE APPLICATION OF BAYES YING-YANG HARMONY BASED GMMS IN ON-LINE SIGNATURE VE...
ijaia
Comparing between maximum
Comparing between maximum
ijseajournal
What is ARIMA Forecasting and How Can it Be Used for Enterprise Analysis?
What is ARIMA Forecasting and How Can it Be Used for Enterprise Analysis?
Smarten Augmented Analytics
A Novel Methodology to Implement Optimization Algorithms in Machine Learning
A Novel Methodology to Implement Optimization Algorithms in Machine Learning
Venkata Karthik Gullapalli
Boston housing data analysis
Boston housing data analysis
Preethi Jayaram Jayaraman
More Related Content
What's hot
P1161208119
P1161208119
Ashraf Aboshosha
Xmr im
Xmr im
Alkis Vazacopoulos
Operational Research
Operational Research
Roy Thomas
Evaluating & Monitoring Your Process Using MSA & SPC
Evaluating & Monitoring Your Process Using MSA & SPC
JMP software from SAS
Car insurance - data visualization
Car insurance - data visualization
Saleesh Satheeshchandran
Efficient Top-N Recommendation for Very Large Scale Binary Rated Datasets
Efficient Top-N Recommendation for Very Large Scale Binary Rated Datasets
Fabio Aiolli
Monte Carlo Simulation Of Heston Model In Matlab(1)
Monte Carlo Simulation Of Heston Model In Matlab(1)
Amir Kheirollah
What's hot
(7)
P1161208119
P1161208119
Xmr im
Xmr im
Operational Research
Operational Research
Evaluating & Monitoring Your Process Using MSA & SPC
Evaluating & Monitoring Your Process Using MSA & SPC
Car insurance - data visualization
Car insurance - data visualization
Efficient Top-N Recommendation for Very Large Scale Binary Rated Datasets
Efficient Top-N Recommendation for Very Large Scale Binary Rated Datasets
Monte Carlo Simulation Of Heston Model In Matlab(1)
Monte Carlo Simulation Of Heston Model In Matlab(1)
Viewers also liked
Confi.pt_LeanProject_MarketAnalysis
Confi.pt_LeanProject_MarketAnalysis
Mariana Taylor de Jesus
обо мне
обо мне
tatsorokina1
Propuesta sobre educaciã“n seguridad vial y participaciã“n comunitaria en la ...
Propuesta sobre educaciã“n seguridad vial y participaciã“n comunitaria en la ...
proyectosdecorazon
Ídolos de la Juventud
Ídolos de la Juventud
angelkuki
Homework 01
Homework 01
MyongJung Kim
A un año de tu partida
A un año de tu partida
UTH
Pasatiempo
Pasatiempo
Caah1967
Viaje de estudios
Viaje de estudios
romariorivera
We're together
We're together
Farizat Torogeldievna
Viewers also liked
(9)
Confi.pt_LeanProject_MarketAnalysis
Confi.pt_LeanProject_MarketAnalysis
обо мне
обо мне
Propuesta sobre educaciã“n seguridad vial y participaciã“n comunitaria en la ...
Propuesta sobre educaciã“n seguridad vial y participaciã“n comunitaria en la ...
Ídolos de la Juventud
Ídolos de la Juventud
Homework 01
Homework 01
A un año de tu partida
A un año de tu partida
Pasatiempo
Pasatiempo
Viaje de estudios
Viaje de estudios
We're together
We're together
Similar to Abstract trisnawati
Performance improvement of a Rainfall Prediction Model using Particle Swarm O...
Performance improvement of a Rainfall Prediction Model using Particle Swarm O...
ijceronline
THE APPLICATION OF BAYES YING-YANG HARMONY BASED GMMS IN ON-LINE SIGNATURE VE...
THE APPLICATION OF BAYES YING-YANG HARMONY BASED GMMS IN ON-LINE SIGNATURE VE...
ijaia
Comparing between maximum
Comparing between maximum
ijseajournal
What is ARIMA Forecasting and How Can it Be Used for Enterprise Analysis?
What is ARIMA Forecasting and How Can it Be Used for Enterprise Analysis?
Smarten Augmented Analytics
A Novel Methodology to Implement Optimization Algorithms in Machine Learning
A Novel Methodology to Implement Optimization Algorithms in Machine Learning
Venkata Karthik Gullapalli
Boston housing data analysis
Boston housing data analysis
Preethi Jayaram Jayaraman
Different Models Used In Time Series - InsideAIML
Different Models Used In Time Series - InsideAIML
VijaySharma802
COSMOS-ASME-IDETC-2014
COSMOS-ASME-IDETC-2014
OptiModel
MyPoster1
MyPoster1
Jamie Schreader
Enhance interval width of crime forecasting with ARIMA model-fuzzy alpha cut
Enhance interval width of crime forecasting with ARIMA model-fuzzy alpha cut
TELKOMNIKA JOURNAL
IRJET- Error Reduction in Data Prediction using Least Square Regression Method
IRJET- Error Reduction in Data Prediction using Least Square Regression Method
IRJET Journal
The Application Of Bayes Ying-Yang Harmony Based Gmms In On-Line Signature Ve...
The Application Of Bayes Ying-Yang Harmony Based Gmms In On-Line Signature Ve...
ijaia
Using genetic algorithms and simulation as decision support in marketing stra...
Using genetic algorithms and simulation as decision support in marketing stra...
infopapers
APPROACHES IN USING EXPECTATIONMAXIMIZATION ALGORITHM FOR MAXIMUM LIKELIHOOD ...
APPROACHES IN USING EXPECTATIONMAXIMIZATION ALGORITHM FOR MAXIMUM LIKELIHOOD ...
cscpconf
韩国会议
韩国会议
YAO YUAN
Applications Residual Control Charts Based on Variable Limits
Applications Residual Control Charts Based on Variable Limits
IJERA Editor
difference between dynamic programming and divide and conquer
difference between dynamic programming and divide and conquer
SRISHTISRIVASTAVA212
Deep_Learning__INAF_baroncelli.pdf
Deep_Learning__INAF_baroncelli.pdf
asdfasdf214078
COSMOS1_Scitech_2014_Ali
COSMOS1_Scitech_2014_Ali
MDO_Lab
AMS_Aviation_2014_Ali
AMS_Aviation_2014_Ali
MDO_Lab
Similar to Abstract trisnawati
(20)
Performance improvement of a Rainfall Prediction Model using Particle Swarm O...
Performance improvement of a Rainfall Prediction Model using Particle Swarm O...
THE APPLICATION OF BAYES YING-YANG HARMONY BASED GMMS IN ON-LINE SIGNATURE VE...
THE APPLICATION OF BAYES YING-YANG HARMONY BASED GMMS IN ON-LINE SIGNATURE VE...
Comparing between maximum
Comparing between maximum
What is ARIMA Forecasting and How Can it Be Used for Enterprise Analysis?
What is ARIMA Forecasting and How Can it Be Used for Enterprise Analysis?
A Novel Methodology to Implement Optimization Algorithms in Machine Learning
A Novel Methodology to Implement Optimization Algorithms in Machine Learning
Boston housing data analysis
Boston housing data analysis
Different Models Used In Time Series - InsideAIML
Different Models Used In Time Series - InsideAIML
COSMOS-ASME-IDETC-2014
COSMOS-ASME-IDETC-2014
MyPoster1
MyPoster1
Enhance interval width of crime forecasting with ARIMA model-fuzzy alpha cut
Enhance interval width of crime forecasting with ARIMA model-fuzzy alpha cut
IRJET- Error Reduction in Data Prediction using Least Square Regression Method
IRJET- Error Reduction in Data Prediction using Least Square Regression Method
The Application Of Bayes Ying-Yang Harmony Based Gmms In On-Line Signature Ve...
The Application Of Bayes Ying-Yang Harmony Based Gmms In On-Line Signature Ve...
Using genetic algorithms and simulation as decision support in marketing stra...
Using genetic algorithms and simulation as decision support in marketing stra...
APPROACHES IN USING EXPECTATIONMAXIMIZATION ALGORITHM FOR MAXIMUM LIKELIHOOD ...
APPROACHES IN USING EXPECTATIONMAXIMIZATION ALGORITHM FOR MAXIMUM LIKELIHOOD ...
韩国会议
韩国会议
Applications Residual Control Charts Based on Variable Limits
Applications Residual Control Charts Based on Variable Limits
difference between dynamic programming and divide and conquer
difference between dynamic programming and divide and conquer
Deep_Learning__INAF_baroncelli.pdf
Deep_Learning__INAF_baroncelli.pdf
COSMOS1_Scitech_2014_Ali
COSMOS1_Scitech_2014_Ali
AMS_Aviation_2014_Ali
AMS_Aviation_2014_Ali
More from ekaputragunartha
Ringkasan vanili
Ringkasan vanili
ekaputragunartha
Ringkasan faktor determinan hara batuan silikat
Ringkasan faktor determinan hara batuan silikat
ekaputragunartha
Abstract anna apriana hidayanti
Abstract anna apriana hidayanti
ekaputragunartha
Intisari anna apriana hidayanti
Intisari anna apriana hidayanti
ekaputragunartha
Abstract bq mina utama sari
Abstract bq mina utama sari
ekaputragunartha
Intisari bq mina utama sari
Intisari bq mina utama sari
ekaputragunartha
Abstract farwan
Abstract farwan
ekaputragunartha
Intisari farwan
Intisari farwan
ekaputragunartha
Abstract mikhratunnisa
Abstract mikhratunnisa
ekaputragunartha
Intisari mikhratunnisa
Intisari mikhratunnisa
ekaputragunartha
Intisari trisnawati
Intisari trisnawati
ekaputragunartha
Abstract bq diah fitasari
Abstract bq diah fitasari
ekaputragunartha
Intisari bq diah fitasari
Intisari bq diah fitasari
ekaputragunartha
Abstract kusni apriliani
Abstract kusni apriliani
ekaputragunartha
Intisari kusni apriliani
Intisari kusni apriliani
ekaputragunartha
Abstract farida nursanti as
Abstract farida nursanti as
ekaputragunartha
Intisari farida nursanti as
Intisari farida nursanti as
ekaputragunartha
Abstract sri hartati ningsih
Abstract sri hartati ningsih
ekaputragunartha
Intisari sri hartati ningsih
Intisari sri hartati ningsih
ekaputragunartha
Abstract emy fitryani
Abstract emy fitryani
ekaputragunartha
More from ekaputragunartha
(20)
Ringkasan vanili
Ringkasan vanili
Ringkasan faktor determinan hara batuan silikat
Ringkasan faktor determinan hara batuan silikat
Abstract anna apriana hidayanti
Abstract anna apriana hidayanti
Intisari anna apriana hidayanti
Intisari anna apriana hidayanti
Abstract bq mina utama sari
Abstract bq mina utama sari
Intisari bq mina utama sari
Intisari bq mina utama sari
Abstract farwan
Abstract farwan
Intisari farwan
Intisari farwan
Abstract mikhratunnisa
Abstract mikhratunnisa
Intisari mikhratunnisa
Intisari mikhratunnisa
Intisari trisnawati
Intisari trisnawati
Abstract bq diah fitasari
Abstract bq diah fitasari
Intisari bq diah fitasari
Intisari bq diah fitasari
Abstract kusni apriliani
Abstract kusni apriliani
Intisari kusni apriliani
Intisari kusni apriliani
Abstract farida nursanti as
Abstract farida nursanti as
Intisari farida nursanti as
Intisari farida nursanti as
Abstract sri hartati ningsih
Abstract sri hartati ningsih
Intisari sri hartati ningsih
Intisari sri hartati ningsih
Abstract emy fitryani
Abstract emy fitryani
Recently uploaded
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17
Celine George
Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptx
NirmalaLoungPoorunde1
DATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginners
Sabitha Banu
Meghan Sutherland In Media Res Media Component
Meghan Sutherland In Media Res Media Component
InMediaRes1
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
pboyjonauth
CELL CYCLE Division Science 8 quarter IV.pptx
CELL CYCLE Division Science 8 quarter IV.pptx
JiesonDelaCerna
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon A
UnboundStockton
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
iammrhaywood
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdf
Mahmoud M. Sallam
Hierarchy of management that covers different levels of management
Hierarchy of management that covers different levels of management
mkooblal
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
socialsciencegdgrohi
Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17
Celine George
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
Virag Sontakke
Painted Grey Ware.pptx, PGW Culture of India
Painted Grey Ware.pptx, PGW Culture of India
Virag Sontakke
Capitol Tech U Doctoral Presentation - April 2024.pptx
Capitol Tech U Doctoral Presentation - April 2024.pptx
CapitolTechU
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
RaymartEstabillo3
internship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developer
unnathinaik
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptx
thorishapillay1
Solving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptx
OH TEIK BIN
OS-operating systems- ch04 (Threads) ...
OS-operating systems- ch04 (Threads) ...
Dr. Mazin Mohamed alkathiri
Recently uploaded
(20)
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17
Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptx
DATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginners
Meghan Sutherland In Media Res Media Component
Meghan Sutherland In Media Res Media Component
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
CELL CYCLE Division Science 8 quarter IV.pptx
CELL CYCLE Division Science 8 quarter IV.pptx
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon A
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdf
Hierarchy of management that covers different levels of management
Hierarchy of management that covers different levels of management
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
Painted Grey Ware.pptx, PGW Culture of India
Painted Grey Ware.pptx, PGW Culture of India
Capitol Tech U Doctoral Presentation - April 2024.pptx
Capitol Tech U Doctoral Presentation - April 2024.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
internship ppt on smartinternz platform as salesforce developer
internship ppt on smartinternz platform as salesforce developer
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptx
Solving Puzzles Benefits Everyone (English).pptx
Solving Puzzles Benefits Everyone (English).pptx
OS-operating systems- ch04 (Threads) ...
OS-operating systems- ch04 (Threads) ...
Abstract trisnawati
1.
ABSTRACT Trisnawati,
2012.-- ARIMA MODEL PARAMETER ESTIMATION OF COMPOSITE STOCK EXCHANGE INDEX USING BOOTSTRAP METHOD (i – xiv; 105 pages) (Supervisors : I Gde Ekaputra Gunartha and Mustika Hadijati) The study aims to find the composite stock exchange index (CSEI) ARIMA model using bootstrap method and to determine the amount of replication (B) which has a significantly minimum bootstrap standard error. The data used in this study are data CSEI on period of January 3 to June 30, 2011. This study consists of several stages, namely: ARIMA model identification, parameter estimation, estimation of parameter model selected using bootstrap methods, and diagnostic checking. From model identification stage was selected CSEI ARIMA model (2,1,0) without constant. Model parameters were estimated by Ordinary Least Square method (OLS) and Maximum Likelihood Estimation (MLE) using the software Minitab 15. The standard error (SE) of ARIMA model selected then compared with the estimation results using the bootstrap method. The number of replication (B) examined to obtain a significant minimum SE were 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900, 2000, 2100, 2200, 2300, 2400, and 2500 replicate. The analysis used the S-Plus 2000. The results of study showed ARIMA model for periodic data of CSEI using bootstrap methods as follows: 1. For the OLS algorithm obtained ARIMA model: X t X t 1 0,1717 X t 1 X t 2 0,1698 X t 2 X t 3 ˆ 2. For the MLE algorithm obtained ARIMA model: X t X t 1 0,6659 X t 1 X t 2 0,3402 X t 2 X t 3 ˆ Bootstrap method can reduce the standard error of 39.91% in the ARIMA model with OLS. While the MLE, the bootstrap method is not great influence on changes in the value of its SE. Thus the bootstrap method is very well applied to the ARIMA model- based estimates of OLS. Based on the results of standard error calculation for each model above obtained the number of B in the re-sampling process of bootstrap methods that has a significantly minimum of SE is 1000 replicate. Keywords: ARIMA, bootstrap, resampling © Program Studi Matematika – FMIPA Universitas Mataram (2012)
Download now