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Longitudinal Data Analysis and Time Series Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
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- Multivariate Models in Marketing (4)
- Copula Modeling (3)
- Forecasting and Time Series (2)
- Bayesian Estimation; Discrete Copula; Markov chain Monte Carlo; Gaussian Copula; Media Modeling; Probability Models; Website Page Views (1)
- Bayesian Model Averaging and Semiparametric Regression (1)
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- Diagnostic check (1)
- Functional Connectivity (1)
- Gaussian Discrete Copula using Bayesian MCMC (1)
- Monte-Carlo significance test (1)
- Multivariate time series (1)
- Parallel computing and multi-core systems (1)
- Periodogram matrix (1)
- Portmanteau test (1)
- Residual autocorrelation function (1)
- Shrinkage (1)
- Spectral density matrix (1)
- Time Series (1)
- VARMAmodels (1)
- Vector autoregressive model. (1)
- Volatility Modeling (1)
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Articles 1 - 9 of 9
Full-Text Articles in Longitudinal Data Analysis and Time Series
Diagnostic Checking, Time Series And Regression, Esam Mahdi
Diagnostic Checking, Time Series And Regression, Esam Mahdi
Electronic Thesis and Dissertation Repository
In this thesis, a new univariate-multivariate portmanteau test is derived. The proposed test statistic can be used for diagnostic checking ARMA, VAR, FGN, GARCH, and TAR time series models as well as for checking randomness of series and goodness-of- fit VAR models with stable Paretian errors. The asymptotic distribution of the test statistic is derived as well as a chi-square approximation. However, the Monte-Carlo test is recommended unless the series is very long. Extensive simulation experiments demonstrate the usefulness of this test and its improved power performance compared to widely used previous multivariate portmanteau diagnostic check. The contributed R package …
Applying Localized Realized Volatility Modeling To Futures Indices, Luella Fu
Applying Localized Realized Volatility Modeling To Futures Indices, Luella Fu
CMC Senior Theses
This thesis extends the application of the localized realized volatility model created by Ying Chen, Wolfgang Karl Härdle, and Uta Pigorsch to other futures markets, particularly the CAC 40 and the NI 225. The research attempted to replicate results though ultimately, those results were invalidated by procedural difficulties.
Rejoinder: Estimation Issues For Copulas Applied To Marketing Data, Peter Danaher, Michael Smith
Rejoinder: Estimation Issues For Copulas Applied To Marketing Data, Peter Danaher, Michael Smith
Michael Stanley Smith
Estimating copula models using Bayesian methods presents some subtle challenges, ranging from specification of the prior to computational tractability. There is also some debate about what is the most appropriate copula to employ from those available. We address these issues here and conclude by discussing further applications of copula models in marketing.
Forecasting Television Ratings, Peter Danaher, Tracey Dagger, Michael Smith
Forecasting Television Ratings, Peter Danaher, Tracey Dagger, Michael Smith
Michael Stanley Smith
Despite the state of flux in media today, television remains the dominant player globally for advertising spend. Since television advertising time is purchased on the basis of projected future ratings, and ad costs have skyrocketed, there is increasing pressure to forecast television ratings accurately. Previous forecasting methods are not generally very reliable and many have not been validated, but more distressingly, none have been tested in today’s multichannel environment. In this study we compare 8 different forecasting models, ranging from a naïve empirical method to a state-of-the-art Bayesian model-averaging method. Our data come from a recent time period, 2004-2008 in …
An Autoregressive Approach To House Price Modeling, Chaitra Nagaraja, Lawrence Brown, Linda Zhao
An Autoregressive Approach To House Price Modeling, Chaitra Nagaraja, Lawrence Brown, Linda Zhao
Chaitra H Nagaraja
No abstract provided.
Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith
Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith
Michael Stanley Smith
This is an example Windows 32bit program to estimate a Gaussian copula model with NBD margins. The margins are estimated first using MLE, and the copula second using Bayesian MCMC. The model was discussed in Danaher & Smith (2011; Marketing Science) as example 4 (section 4.2).
Modeling Multivariate Distributions Using Copulas: Applications In Marketing, Peter J. Danaher, Michael S. Smith
Modeling Multivariate Distributions Using Copulas: Applications In Marketing, Peter J. Danaher, Michael S. Smith
Michael Stanley Smith
In this research we introduce a new class of multivariate probability models to the marketing literature. Known as “copula models”, they have a number of attractive features. First, they permit the combination of any univariate marginal distributions that need not come from the same distributional family. Second, a particular class of copula models, called “elliptical copula”, have the property that they increase in complexity at a much slower rate than existing multivariate probability models as the number of dimensions increase. Third, they are very general, encompassing a number of existing multivariate models, and provide a framework for generating many more. …
Bicycle Commuting In Melbourne During The 2000s Energy Crisis: A Semiparametric Analysis Of Intraday Volumes, Michael S. Smith, Goeran Kauermann
Bicycle Commuting In Melbourne During The 2000s Energy Crisis: A Semiparametric Analysis Of Intraday Volumes, Michael S. Smith, Goeran Kauermann
Michael Stanley Smith
Cycling is attracting renewed attention as a mode of transport in western urban environments, yet the determinants of usage are poorly understood. In this paper we investigate some of these using intraday bicycle volumes collected via induction loops located at ten bike paths in the city of Melbourne, Australia, between December 2005 and June 2008. The data are hourly counts at each location, with temporal and spatial disaggregation allowing for the impact of meteorology to be measured accurately for the first time. Moreover, during this period petrol prices varied dramatically and the data also provide a unique opportunity to assess …
The Generalized Shrinkage Estimator For The Analysis Of Functional Connectivity Of Brain Signals, Mark Fiecas, Hernando Ombao
The Generalized Shrinkage Estimator For The Analysis Of Functional Connectivity Of Brain Signals, Mark Fiecas, Hernando Ombao
Mark Fiecas
We develop a new statistical method for estimating functional connectivity between neurophysiological signals represented by a multivariate time series. We use partial coherence as the measure of functional connectivity. Partial coherence identifies the frequency bands that drive the direct linear association between any pair of channels. To estimate partial coherence, one would first need an estimate of the spectral density matrix of the multivariate time series. Parametric estimators of the spectral density matrix provide good frequency resolution but could be sensitive when the parametric model is misspecified. Smoothing-based nonparametric estimators are robust to model misspecification and are consistent but may …