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14 articles for “heteroscedastic”
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Research ArticleOpen accessEvery word in the titleA NOVEL ROBUST AND EFFICIENT TOOL FOR DETECTING HETEROSCEDASTICITYWei Xiong, Maozai TianOne of the greatest values of Quantile Regression (QR) is that it provides a good procedure in the sense that QR could be much more efficient and sometimes arbitrarily more efficient in recovering the mean function than the Least Squares (LS) even when without moment conditions. However, heteroscedasticity definitely causes conditional variances of parametric or nonparametric estimates of mean functions … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Mar 2014 · 6,657 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSpline Smoothing for Multi-Response Nonparametric Regression Model in Case of Heteroscedasticity of VarianceBudi Lestari, I. Nyoman Budiantara, Sony Sunaryo, Muhammad MashuriProblem statement: Assume that data (yki, tki), k = 1,2,…, p; i = 1,2,…,nk where nk represents the number of repeated measurement of kth object follows multi-response nonparametric regression model with variances of errors are heteroscedastic. Nonparametric regression curves are unknown and assumed to be smooth which are contained in Sobolev space. Random Errors are independent and normally distributed with … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 13 Oct 2012 · 7,955 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Robust Modification of the Goldfeld-Quandt Test for the Detection of Heteroscedasticity in the Presence of OutliersMd. Sohel Rana, Habshah Midi, A.H.M. Rahmatullah ImonProblem statement: The problem of heteroscedasticity occurs in regression analysis for many practical reasons. It is now evident that the heteroscedastic problem affects both the estimation and test procedure of regression analysis, so it is really important to be able to detect this problem for possible remedy. The existence of a few extreme or unusual observations that we often call … …Journal of Mathematics and Statistics, Vol. 4, Issue 4 · 31 Dec 2008 · 7,936 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleModeling the Error Term by Moving Average and Generalized Autoregressive Conditional Heteroscedasticity ProcessesAyodele Abraham Agboluaje, Suzilah bt Ismail, Chee Yin YipThis study has been able to reveal that the Combine White Noise model outperforms the existing Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Moving Average (MA) models in modeling the errors, that exhibits conditional heteroscedasticity and leverage effect. MA process cannot model the data that reveals conditional heteroscedasticity and GARCH cannot model the leverage effect also. The standardized residuals of GARCH … …American Journal of Applied Sciences, Vol. 12, Issue 11 · 20 Nov 2015 · 6,721 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDAILY CRUDE OIL PRICE FORECASTING MODEL USING ARIMA, GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC AND SUPPORT VECTOR MACHINESRana Abdullah Ahmed, Ani Bin ShabriCrude oil price forecasting is gaining increased interest globally. This interest is due mainly to the economic value attached to the product. For this reason, new forecasting methods are proposed in the literature. This paper proposes a novel technique for forecasting crude oil price based on Support Vector Machines (SVM). The study adopts the data on crude oil price of … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 11 Jan 2014 · 8,725 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Effect of Socioeconomic and Demographic Factors on Contraceptive Use and Induced Abortion in TurkeyOzlem Alpu, Gunseli KurtThe aim of the study was to estimate the parameters of the heteroscedastic bivariate Probit model established for the induced abortion and the contraceptive use by using socioeconomic and demographic factors and their effects by eliminating the observed heteroscedasticity. Using a heteroscedastic bivariate Probit model and Turkish Demographic and Health Survey (1998) data on married women aged 15 through 49 … …American Journal of Applied Sciences, Vol. 1, Issue 4 · 31 Dec 2004 · 6,719 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Generalized Discrete-Time Long Memory Volatility Model for Financial Stock ExchangeChin Wen CheongWe proposed a simple way to combine a few long memory models in financial market volatility modeling using daily, range and high frequency data. This model was able to fit the return, range of daily return or realized volatility under a parametric heavy-tailed distribution. Model was flexible to include additional volatility information as the contemporaneous variables. Empirical results found that … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 6,869 accessesView PDFCite
Research ArticleOpen accessIn the abstractPoisson Quasi-Maximum Likelihood Estimator-based CUSUM Test for Integer-Valued Time SeriesSangyeol LeeThis study considers the parameter change test for integer-valued time series models based on the Poisson quasi-maximum likelihood estimates. As a change point test, we consider the score vector-based CUSUM test and show that its limiting null distribution takes the form of a function of Brownian bridges. Moreover, the residual-based CUSUM tests are considered as alternatives. For evaluation, we conduct … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 1 Oct 2019 · 7,650 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Based Feature Selection of Macroeconomic Variables for Stock Market PredictionIsaac Kofi Nti, Adebayo Felix Adekoya, Benjamin Asubam WeyoriA firm’s equity price on the stock-market is reported to be closely related to the Macroeconomic Variable (MVs) of the country in which the firm trades. For this reason, researchers, market traders, financial analysts and forecasters to examine the association between MVs and stock-price have carried out numerous studies, using time-series statistical analysis methods like Autoregressive Integrated Moving Average (ARIMA), … …American Journal of Applied Sciences, Vol. 16, Issue 7 · 31 Jul 2019 · 10,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Size and Power of Eight Normality Tests in Presence of GARCH (1 1) ErrorsJulio César Alonso, Daniela EstradaIn this work, we assess the power and size of eight normality tests underthe assumption that errors follow a GARCH (1, 1) process by using MonteCarlo simulations. Four results stand out. First, the presence of a GARCH(1, 1) process increases the probability of making type I error. Second, Pearsonnormality test is recommended if it is assumed that errors follow a … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 11 Feb 2019 · 6,992 accessesView PDFCite