84 research outputs found
The Dependent Poisson Race Model and Modeling Dependence in Conjoint Choice Experiments
No full textBayesian model, dependent processes, dominance, multinomial logit model, Poisson process,
sj-docx-2-han-10.1177_15589447211066347 – Supplemental material for The Current State of Fat Grafting in the Hand: A Systematic Review for Hand Diseases
No full textSupplemental material, sj-docx-2-han-10.1177_15589447211066347 for The Current State of Fat Grafting in the Hand: A Systematic Review for Hand Diseases by Alexander N. Khouri, Widya Adidharma, Mark MacEachern, Steven C. Haase, Jennifer F. Waljee, Paul S. Cederna and Amy L. Strong in HAND</p
sj-docx-1-han-10.1177_15589447211066347 – Supplemental material for The Current State of Fat Grafting in the Hand: A Systematic Review for Hand Diseases
No full textSupplemental material, sj-docx-1-han-10.1177_15589447211066347 for The Current State of Fat Grafting in the Hand: A Systematic Review for Hand Diseases by Alexander N. Khouri, Widya Adidharma, Mark MacEachern, Steven C. Haase, Jennifer F. Waljee, Paul S. Cederna and Amy L. Strong in HAND</p
Efficient quantile regression for heteroscedastic models
No full textQuantile regression (QR) provides estimates of a range of conditional quantiles. This stands in contrast to traditional regression techniques, which focus on a single conditional mean function. Lee et al. [Regularization of case-specific parameters for robustness and efficiency. Statist Sci. 2012;27(3):350–372] proposed efficient QR by rounding the sharp corner of the loss. The main modification generally involves an asymmetric ℓ₂ adjustment of the loss function around zero. We extend the idea of ℓ₂ adjusted QR to linear heterogeneous models. The ℓ₂ adjustment is constructed to diminish as sample size grows. Conditions to retain consistency properties are also provided
Subsampling the Gibbs sampler: variance reduction
No full textSubsampling the output of a Gibbs sampler in a non-systematic fashion can improve the efficiency of marginal estimators if the subsampling strategy is tied to the actual updates made. We illustrate this point by example, approximation, and asymptotics. The results hold both for random-scan and fixed-scan Gibbs samplers.Bayesian analysis Efficiency Estimation Markov chains Monte Carlo Stationary time series
A regression approach to the two-dataset problem
No full textThis paper considers the two-dataset problem, where data are collected from
two potentially different populations sharing common aspects. This problem
arises when data are collected by two different types of researchers or from
two different sources. We may reach invalid conclusions without using knowledge
about the data collection process. To address this problem, this paper develops
statistical regression models focusing on the difference in measurement and
proposes two prediction errors that help to evaluate the underlying data
collection process. As a consequence, it is possible to discuss the
heterogeneity/similarity of the set of predictors in terms of prediction. Two
real datasets are selected to illustrate our method.Comment: The final version will be published in Statistic
Development of a novel precision applicator for spot treatment of granular agrochemical in wild blueberry
No full textWhile spot spraying has gained increasing popularity in recent years, spot application of granule agrochemical has seen little development. Despite the potential for the technology, there currently exists no commercially available granular applicators capable of spot application. Therefore, the goal of this study was to design, build, and lab evaluate a precision applicator for spot applying granular agrochemical in wild blueberry. The design incorporated a John Deere RC2000 with a custom control box, recirculation system, and electrically actuated valves. All components were modified to fit a Valmar 1255 Twin-Roller. The system receives inputs from a predeveloped prescription map and can actuate each of the twelve valves separately to provide individual orifice control. Casoron® G4 was used as the testing agrochemical and in cycling the product pneumatically for 1 hour incurred no significant product degradation (p = 0.110). In lab evaluations, the applicator encountered zero errors in reading prescription maps and actuating the correct valves accordingly. Further, the granule recycling system had zero instances where product built up in the lines or jammed the valves. In all, this project represents the first successful development of a precision granular spot applicator for any cropping system.New Brunswick Canadian Agricultural Partnership (CAP)Natural Sciences and Engineering Research Council (NSERC) of Canada Discovery Grants ProgramWild Blueberry Producers Association of Nova Scotia (WBPANS
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