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Articles 1 - 8 of 8
Full-Text Articles in Social and Behavioral Sciences
A Mixture Autoregressive Model Based On Student’S T–Distribution, Mika Meitz, Daniel Preve, Pentti Saikkonen
A Mixture Autoregressive Model Based On Student’S T–Distribution, Mika Meitz, Daniel Preve, Pentti Saikkonen
Research Collection School Of Economics
A new mixture autoregressive model based on Student’s t–distribution is proposed. A key feature of our model is that the conditional t–distributions of the component models are based on autoregressions that have multivariate t–distributions as their (low-dimensional) stationary distributions. That autoregressions with such stationary distributions exist is not immediate. Our formulation implies that the conditional mean of each component model is a linear function of past observations and the conditional variance is also time-varying. Compared to previous mixture autoregressive models our model may therefore be useful in applications where the data exhibits rather strong conditional heteroskedasticity. Our formulation also has …
Discrete Processing In Visual Perception, Marshall L. Green
Discrete Processing In Visual Perception, Marshall L. Green
Theses and Dissertations
Two very different classes of theoretical models have been proposed to explain visual perception. One class of models assume that there is a point at which we become consciously aware of a stimulus, known as a threshold. This threshold is the foundation of discrete process models all of which describe an all-or-none transition between the mental state of perceiving a stimulus and the state of not perceiving a stimulus. In contrast, the other class of models assume that mental states change continuously. These continuous models are founded in signal detection theory and the more contemporary models in Bayesian inference frameworks. …
Estimation Of Zero-Inflated Population Mean: A Bootstrapping Approach, Khyam Paneru, R. Noah Padgett, Hanfeng Chen
Estimation Of Zero-Inflated Population Mean: A Bootstrapping Approach, Khyam Paneru, R. Noah Padgett, Hanfeng Chen
Journal of Modern Applied Statistical Methods
A mixture model was adopted from the maximum pseudo-likelihood approach under complex sampling designs to estimate the mean of zero-inflated population. To overcome the complexity and assumptions of asymptotic distribution, the maximum pseudo-likelihood function was used, but a bootstrapping procedure was proposed as an alternative. Bootstrap confidence intervals consistently capture the true means of zero-inflated populations of the simulation studies.
Doubly Censored Data From Two-Component Mixture Of Inverse Weibull Distributions: Theory And Applications, Tabassum Sindhu, Navid Feroze, Muhammad Aslam
Doubly Censored Data From Two-Component Mixture Of Inverse Weibull Distributions: Theory And Applications, Tabassum Sindhu, Navid Feroze, Muhammad Aslam
Journal of Modern Applied Statistical Methods
Finite mixture distributions consist of a weighted sum of standard distributions and are a useful tool for reliability analysis of a heterogeneous population. They provide the necessary flexibility to model failure distributions of components with multiple failure models. The analysis of the mixture models under Bayesian framework has received sizable attention in the recent years. However, the Bayesian estimation of the mixture models under doubly censored samples has not yet been introduced in the literature. The main objective of this paper is to discuss the Bayes estimation of the inverse Weibull mixture distributions under doubly censoring. Different priors and loss …
A Mixture Model Demonstrates Use Of Distinct Strategies In A Global Motion Direction Task, Lanya Tianhao Cai, Benjamin T. Backus
A Mixture Model Demonstrates Use Of Distinct Strategies In A Global Motion Direction Task, Lanya Tianhao Cai, Benjamin T. Backus
MODVIS Workshop
Mixture models are well known in cognitive psychology, less so in vision. Are there cases where the data allow clear testing as to whether different strategies are employed in a task? Most psychophysical measurements manipulate a single staircase variable to map out a monotonic increasing function, but if performance is limited by different mechanisms over the range of the variable, classical fitting could be inappropriate. We present a data set and analyses that confirm the presence of two visual strategies addressing the same task, with the choice of strategies depending on the staircase variable. In a net-motion discrimination task, stimuli …
Extending An Irt Mixture Model To Detect Random Responders On Non-Cognitive Polytomously Scored Assessments, Mandalyn R. Swanson
Extending An Irt Mixture Model To Detect Random Responders On Non-Cognitive Polytomously Scored Assessments, Mandalyn R. Swanson
Dissertations, 2014-2019
This study represents an attempt to distinguish two classes of examinees – random responders and valid responders – on non-cognitive assessments in low-stakes testing. The majority of existing literature regarding the detection of random responders in low-stakes settings exists in regard to cognitive tests that are dichotomously scored. However, evidence suggests that random responding occurs on non-cognitive assessments, and as with cognitive measures, the data derived from such measures are used to inform practice. Thus, a threat to test score validity exists if examinees’ response selections do not accurately reflect their underlying level on the construct being assessed. As with …
Bayesian Estimation Of The Parameters Of Two-Component Mixture Of Rayleigh Distribution Under Doubly Censoring, Tahassum N. Sindhu, Navid Feroze, Muhammad Aslam
Bayesian Estimation Of The Parameters Of Two-Component Mixture Of Rayleigh Distribution Under Doubly Censoring, Tahassum N. Sindhu, Navid Feroze, Muhammad Aslam
Journal of Modern Applied Statistical Methods
Recently, the Bayesian analysis of the two-component mixture of lifetime models under singly type I censored samples was discussed. The Bayes estimation of the parameters of mixture of two Rayleigh distributions (MTRD) is developed under doubly censoring. Different informative priors, under squared error loss function and k-loss function, have been assumed for the posterior estimation. The performance of different estimators has been compared in terms of posterior risks by analyzing the simulated and real life data sets.
Obtaining Critical Values For Test Of Markov Regime Switching, Douglas G. Steigerwald, Valerie Bostwick
Obtaining Critical Values For Test Of Markov Regime Switching, Douglas G. Steigerwald, Valerie Bostwick
Douglas G. Steigerwald
For Markov regime-switching models, testing for the possible presence of more than one regime requires the use of a non-standard test statistic. Carter and Steigerwald (forthcoming, Journal of Econometric Methods) derive in detail the analytic steps needed to implement the test ofMarkov regime-switching proposed by Cho and White (2007, Econometrica). We summarize the implementation steps and address the computational issues that arise. A new command to compute regime-switching critical values, rscv, is introduced and presented in the context of empirical research.