Determinants of gold price: using simple and multiple linear regression

QR Code

Determinants of gold price: using simple and multiple linear regression

Bibliographic Details
Main Authors:	Choong, Pik San, Kwoo, Pui Yee, Piong, Chee Keai, Wong, Wen Xuan
Format:	Final Year Project / Dissertation / Thesis
Published:	2012
Subjects:	HF Commerce
Online Access:	http://eprints.utar.edu.my/1097/ http://eprints.utar.edu.my/1097/1/BF%2D2012%2D0905944.pdf

Similar Items

Forecasting gold prices using multiple linear regression method
by: Ismail, Zuhaimy, et al.
Published: (2009)

Hedonic house pricing with multiple regression analysis in different states of Malaysia / Lee Soong Lim
by: Lee, Soong Lim
Published: (2012)

Multiple outliers detection procedures in linear regression
by: Adnan, Robiah, et al.
Published: (2003)

Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling
by: Mohd Ibrahim, Mohamad Shafiq, et al.
Published: (2018)

Prediction Of PM10 Using Multiple Linear Regression And Boosted Regression Trees
by: Hamid, Nur Haziqah Mohd
Published: (2017)

Determine the parameters for photoelectric effect data using correlation and simple linear regression
by: Saratha Sathasivam,, et al.
Published: (2022)

Distributionally robust L1-estimation in multiple linear regression
by: Gong, Z., et al.
Published: (2018)

Cluster-Based Estimators For Multiple And Multivariate Linear Regression Models
by: Alih, Ekele
Published: (2015)

Detection of multiple outliners in linear regression using nonparametric methods
by: Adnan, Robiah
Published: (2004)

JMASM 46: Algorithm for comparison of robust regression methods in multiple linear regression by weighting least Square Regression
by: Mohd Ibrahim, Mohamad Shafiq, et al.
Published: (2017)

K-means clustering analysis and multiple linear regression model on household income in Malaysia
by: Gan Pei Yee, Gan Pei Yee, et al.
Published: (2023)

K-means clustering analysis and multiple linear regression model on household income in Malaysia
by: Gan Pei Yee, Gan Pei Yee, et al.
Published: (2023)

K-means clustering analysis and multiple linear regression model on household income in Malaysia
by: Gan Pei Yee, Gan Pei Yee, et al.
Published: (2023)

Multiple linear regression modelling of hot water extraction of soursop juice
by: Quek, Meei Chien, et al.
Published: (2012)

Identifying multiple outliers in linear regression : Robust fit and clustering approach
by: Adnan, Robiah, et al.
Published: (2001)

Combining Geometric Brownian Motion model and multiple linear regression model for predicting Kijang Emas selling price / Basyirah Che Mat
by: Che Mat, Basyirah
Published: (2016)

Enhancing electricity consumption forecasting in limited dataset: A simple stacked ensemble approach incorporating simple linear and support vector regression for Malaysia
by: Chuan, Zun Liang, et al.
Published: (2025)

JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression
by: Wan Ahmad, Wan Muhamad Amir, et al.
Published: (2016)

Fast improvised influential distance for the identification of influential observations in multiple linear regression
by: Habshah Midi,, et al.
Published: (2021)

Performance comparison of haze prediction using chaos theory and multiple linear regression
by: Hazlina Darman,, et al.
Published: (2024)

Comparison between ANN and multiple linear regression models for prediction of warranty cost
by: Mohd Faaizie, Darmawan, et al.
Published: (2018)

Weighted Maximum Median Likelihood Estimation For Parameters In Multiple Linear Regression Model
by: Mohamed Ramli, Norazan
Published: (2008)

Robust diagnostic and parameter estimation for multiple linear and panel data regression models
by: Sani, Muhammad
Published: (2018)

Comparison between ANN and multiple linear regression models for prediction of warranty cost
by: Darmawan, Mohd Faaizie, et al.
Published: (2018)

Fast improvised influential distance for the identification of influential observations in multiple linear regression
by: Midi, Habshah, et al.
Published: (2021)

Robust statistical procedures for multiple linear regression model in the presence of multicollinearity and outliers
by: Hendi, Hasan Talib Hendi.
Published: (2023)

A remedial measure of multicollinearity in multiple linear regression in the presence of high leverage points
by: Ismaeel, Shelan Saied, et al.
Published: (2024)

The development of a multiple linear regression model for aiding formulation development of solid dispersions
by: Fridgeirsdottir, Gudrun A.
Published: (2018)

Utilizing multiple linear regression technique for interential measure of continuous-based process monitoring
by: Muhammad Ridzuan, Mamat
Published: (2013)

A remedial measure of multicollinearity in multiple linear regression in the presence of high leverage points
by: Saied Ismaeel, Shelan, et al.
Published: (2024)

Determination Of Flow Resistance Coefficient Using Multiple Linear Regression And Genetic Expression Programming
by: Abdul Ghaffar, Ahmad Bakri
Published: (2019)

Prediction Of PM10 Concentration Using Multiple Linear Regression And Support Vector Machine
by: Zailan, Masezatti
Published: (2018)

Prediction Of PM10 Concentration Using Multiple Linear Regression And Bayesian Model Averaging
by: Ismail, Hafizahizzati
Published: (2017)

Prediction of pm10 concentration using multiple linear regression and support vector machine
by: Zailan, Masezatti
Published: (2018)

An application of robust method in multiple linear regression model toward credit card debt
by: Azmi, Nur Amira, et al.
Published: (2018)

The performance of clustering approach with robust mm-estimator for multiple outlier detection in linear regression
by: Mohd. Azmi, Nurulhuda Firdaus, et al.
Published: (2006)

The Role of Talent Management in Employee Retention
by: Yong, Pui Chee
Published: (2017)

Flat Price Prediction using Linear and Random Forest Regression based on Machine Learning Techniques
by: Jui, Julakha Jahan, et al.
Published: (2020)

A predictive model for the population growth of refugees in Asia: a multiple linear regression approach
by: Sulaiman, Suriani, et al.
Published: (2019)

Identification of High Leverage Points in Multiple Linear Regression / Noor Azima Ismail... [et al.]
by: Ismail, Nor Azima, et al.
Published: (2016)