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Online Variational Bayes Inference for High-Dimensional Correlated Data
High-dimensional data with hundreds of thousands of observations are becoming commonplace in many disciplines. The analysis of such data poses many computational challenges,... -
Model parameters.
aSpecified with reference to Cook [30] and Waage et al. [36] using distributions defined in Biosecurity Australia [31]; b Derived from Sapoukhina et al. [37]; c ABS [6], Note... -
Experimental Results.
(a) Summary of experimental groups showing representative images (4–16-cell/morula group shows only an 8-cell embryo), average number of hours post-fertilization (p.f.) each... -
Bridge Designs for Modeling Systems With Low Noise
For deterministic computer simulations, Gaussian process models are a standard procedure for fitting data. These models can be used only when the study design avoids having... -
A Transfer Learning Approach for Predictive Modeling of Degenerate Biological...
Modeling of a new domain can be challenging due to scarce data and high-dimensionality. Transfer learning aims to integrate data of the new domain with knowledge about some... -
Tuning Parameter Selection for the Adaptive Lasso Using ERIC
The adaptive Lasso is a commonly applied penalty for variable selection in regression modeling. Like all penalties though, its performance depends critically on the choice of... -
Simulation parameters.
MBR = MPW = MCV = 100, MCA = WBA. n ∈ {3, 9, 27}, WBA ∈ [0.1, 2], WPC ∈ [0, 20], WCT = 0.1. ⌈n/2⌉ groups of size 1 and ⌊n/2⌋ of size chosen uniformly at random from [1, ⌊n/2⌋].... -
Baseline characteristics.
*School-level deprivation uses the decile assigned to each school by the New Zealand Ministry of Education for funding purposes. It reflects the proportion of students who live... -
Supplementary Material
Supplemental material, Supplementary_Table_1_submission_TAH for Safety and efficacy of nilotinib in routine clinical practice in patients with chronic myeloid leukemia in... -
Sensitivity analyses.
Projected Estimates of Reductions in Cardiovascular Disease from a Dietary Salt Reduction Target of 3 g/day achieved over 30 years (via a linear reduction in intake of 0.1... -
Likelihood Estimation for the INAR(<i>p</i>) Model by Saddlepoint Approximation
Saddlepoint techniques have been used successfully in many applications, owing to the high accuracy with which they can approximate intractable densities and tail probabilities.... -
Study design.
Study type refers to the type of model and the inclusion of risk heterogeneity in the population modelled. Setting/MoT refers to the geographical setting and the mode of... -
Cross-Validation Results.
Comparison of normalized root mean square error (NRMSE), median efficiency (), mean efficiency (), 95th percentile efficiency () and completion rate (CR) for the optimal... -
Classification results
This table contrasts the classification results obtained through generative embedding with those afforded by three conventional methods. As described in the main text, the... -
Summary statistics.
Values are presented as Mean ±SEM. Abbreviations: fWHR [34]; EME [44]; ULh, LLh and Nw [33]; Index 1 [47], Index 2 [48], [50], Index 3 [10], [49], ProcDist [54], [79], DiscSco1...