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Overview of Match Effects (Median RTs) in Experiments 1a to 3b and in Previou...
Overview of Match Effects (Median RTs) in Experiments 1a to 3b and in Previous Studies. -
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,... -
r37980778c78--7a054c9422c04d8cdc5573deceaffacd
Basic statistics of SFN data for the 6-year period between 2001 and 2006. -
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... -
r37980778c78--c705259face9858d66e75f6dfa5071f7
The meeting location for each year is highlighted in parenthesis in the first row. -
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... -
Table S1 - An Analysis of the Abstracts Presented at the Annual Meetings of t...
Top 20 most frequently used words in each NCuts topic cluster. The words in each topic cluster are sorted in descending order of frequencies of usage, which are denoted in... -
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... -
Clinical characteristics of patients.
Mean±SD [25., 50. und 75. percentile in case of non-normal distribution] or number (%). ap<0.05;bp<0.01;cp<0.005;dp<0.001 – comparison between survivors and... -
Within sample and Cross Validation prediction of RTs (http://www.wessa.net/rw...
Within sample and Cross Validation prediction of RTs (http://www.wessa.net/rwasp_vle_software_design.wasp). -
Demographic characteristics of the study population.
Continuous variables are reported as mean ± standard deviation, (5th and 95th percentile); categorical variables are presented as counts and frequencies. Abbreviations: ASA =... -
Appendix S1 - Revisiting Mental Simulation in Language Comprehension: Six Rep...
Validation of data-collection procedure via Mechanical Turk using a lexical-decision task. (DOCX) -
Correction for multiple comparisons on volume and cortical thickness differen...
aNumber of tested structures.bNumber of significant structures after application of correction. -
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⌋].... -
The 10 clusters produced by the NCuts algorithm performed on the nearest-neig...
Abbreviations: HVC = “High Vocal Center”; AD = “Alzheimer's Disease”; REM = “Rapid Eye Movement”; SCN = Suprachiasmatic Nucleus”. The third column of the table shows the... -
Summary of Results.
Summary of results of follicle number counts, mRNA analyses and oxidative stress measures in ovaries of offspring born to mothers undernourished during pregnancy (UNP), during...
