16 papers · ranked by Valyu relevance
Anupreet Porwal, Adrian E. Raftery
Title: Significance Choosing a statistical model and accounting for uncertainty about this choice are important parts of the scientific process and are required for common statistical tasks such as parameter estimation, interval estimation, statistical inference, point prediction, and interval prediction. A canonical…
Rezzy Eko Caraka, Rung-Ching Chen, Su-Wen Huang, Shyue-Yow Chiou + 2 more
'Prana Ugiana Gio' 'Bens Pardamean'] Background In heart data mining and machine learning, dimension reduction is needed to remove multicollinearity. Meanwhile, it has been proven to improve the interpretation of the parameter model. In addition, dimension reduction can also increase the time of computing in high…
Herbert Susmann, Monica Alexander, Leontine Alkema
Title: Summary There is growing interest in producing estimates of demographic and global health indicators in populations with limited data. Statistical models are needed to combine data from multiple data sources into estimates and projections with uncertainty. Diverse modelling approaches have been applied to this…
Bálint Király, Balázs Hangya
Model selection is often implicit: when performing an ANOVA, one assumes that the normal distribution is a good model of the data; fitting a tuning curve implies that an additive and a multiplicative scaler describes the behavior of the neuron; even calculating an average implicitly assumes that the data were sampled…
L. Mark Berliner, Radu Herbei, Christopher K. Wikle, Ralph F. Milliff + 1 more
'Ralph F. Milliff' 'Pablo Martin Rodriguez'] Advances in observational and computational assets have led to revolutions in the range and quality of results in many science and engineering settings. However, those advances have led to needs for new research in treating model errors and assessing their impacts. We…
Marco Gregori, Martijn G. De Jong, Rik Pieters
When surveys contain direct questions about sensitive topics, participants may not provide their true answers. Indirect question techniques incentivize truthful answers by concealing participants’ responses in various ways. The Crosswise Model aims to do this by pairing a sensitive target item with a non-sensitive…
Erlandson Ferreira Saraiva, Valdemiro Piedade Vigas, Mariana Villela Flesch, Mark Gannon + 3 more
'Mariana Villela Flesch' 'Mark Gannon' 'Carlos Alberto de Bragança Pereira' 'Philip Broadbridge' 'Udo Von Toussaint'] Dengue fever is a tropical disease transmitted mainly by the female Aedes aegypti mosquito that affects millions of people every year. As there is still no safe and effective vaccine, currently the best…
Nathan A. Judd, Kalliopi Mylona, Haiming Liu, Andy Hogg + 1 more
Accurate predictions of product sales are essential to the foodservice sector, for planning and saving of resources. In this paper, a zero-inflated negative binomial mixed-effects model with several factors was used to predict the total sales of different product categories, taking into consideration different sites…
Stephen B. Broomell, Sabina J. Sloman, Lisheng He
Behavioral models are instrumental for studying human cognition, yet many inferences derived from such models fail to generalize. We argue that this is driven in part by the increasing complexity of behavioral models, where non-linearities and discontinuities create dynamic parameter interactions that limit the…
Cosmin Safta, Jaideep Ray, Wyatt Bridgman, Yoo Min Park
In this paper, we present a method for estimating the infection-rate of a disease as a spatial-temporal field. Our data comprises time-series case-counts of symptomatic patients in various areal units of a region. We extend an epidemiological model, originally designed for a single areal unit, to accommodate multiple…
Daniel McNeish, Tyler H. Matta
The standardized root mean squared residual (SRMR) is commonly reported to evaluate approximate fit of latent variable models. As traditionally defined, SRMR summarizes the discrepancy between observed covariance elements and implied covariance elements. However, current applications of latent variable models often…
Salah Haridy, Batool Alamassi, Ahmed Maged, Mohammad Shamsuzzaman + 2 more
'Ali Al Owad' 'Hamdi Bashir'] When monitoring manufacturing processes, managing an attribute quality characteristic is easier and faster than a variable quality characteristic. Yet, the economic-statistical design of attribute control charts has attracted much less attention than variable control charts in the…
Andres Dajles, Joseph Cavanaugh, Brian Dennis, Mark L. Taper + 1 more
'Jose Miguel Ponciano'] Most statistical modeling applications involve the consideration of a candidate collection of models based on various sets of explanatory variables. The candidate models may also differ in terms of the structural formulations for the systematic component and the posited probability distributions…
Caiming Wu, Fumin Ren, Da-Lin Zhang, Jing Zhu + 2 more
'Yuxu Chen'] In this report, the development of a Dynamical Statistical Analog Ensemble Forecast model for landfalling typhoon disasters (LTDs) and some applications over coastal China are described. This model consists of the following four elements: (i) obtaining the forecast track of a target landfalling typhoon…
Leo Polansky, Lara Mitchell, Ken B. Newman
1. The resolution at which animal populations can be modeled can be increased when multiple datasets corresponding to different life stages are available, allowing, for example, seasonal instead of annual descriptions of dynamics. However, the abundance estimates used for model fitting can have multiple sources of…
Hamami Loubna, Hafida Goual, Fatimah M. Alghamdi, Manahil SidAhmed Mustafa + 6 more
'Manahil SidAhmed Mustafa' 'Getachew Tekle Mekiso' 'M. Masoom Ali' 'Abdullah H. Al-Nefaie' 'Hassan Alsuhabi' 'Mohamed Ibrahim' 'Haitham M. Yousof'] Frailty models are important for survival data because they allow for the possibility of unobserved heterogeneity problem. The problem of heterogeneity can be existed due…