How to address non-normality: A taxonomy of approaches, reviewed, and illustrated
J Pek, O Wong, ACM Wong - Frontiers in psychology, 2018 - frontiersin.org
The linear model often serves as a starting point for applying statistics in psychology. Often,
formal training beyond the linear model is limited, creating a potential pedagogical gap …
formal training beyond the linear model is limited, creating a potential pedagogical gap …
Anomaly detection by robust statistics
PJ Rousseeuw, M Hubert - Wiley Interdisciplinary Reviews …, 2018 - Wiley Online Library
Real data often contain anomalous cases, also known as outliers. These may spoil the
resulting analysis but they may also contain valuable information. In either case, the ability to …
resulting analysis but they may also contain valuable information. In either case, the ability to …
Impact of climate change on biodiversity loss: global evidence
The present study investigates the impact of climate change on biodiversity loss using global
data consisting of 115 countries. In this study, we measure biodiversity loss using data on …
data consisting of 115 countries. In this study, we measure biodiversity loss using data on …
[HTML][HTML] Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of …
Background Associations between high and low temperatures and increases in mortality
and morbidity have been previously reported, yet no comprehensive assessment of disease …
and morbidity have been previously reported, yet no comprehensive assessment of disease …
The Burden of Proof studies: assessing the evidence of risk
Exposure to risks throughout life results in a wide variety of outcomes. Objectively judging
the relative impact of these risks on personal and population health is fundamental to …
the relative impact of these risks on personal and population health is fundamental to …
Non-convex optimization for machine learning
P Jain, P Kar - Foundations and Trends® in Machine …, 2017 - nowpublishers.com
A vast majority of machine learning algorithms train their models and perform inference by
solving optimization problems. In order to capture the learning and prediction problems …
solving optimization problems. In order to capture the learning and prediction problems …
Detecting multivariate outliers: Use a robust variant of the Mahalanobis distance
A look at the psychology literature reveals that researchers still seem to encounter difficulties
in coping with multivariate outliers. Multivariate outliers can severely distort the estimation of …
in coping with multivariate outliers. Multivariate outliers can severely distort the estimation of …
To tune or not to tune the number of trees in random forest
P Probst, AL Boulesteix - Journal of Machine Learning Research, 2018 - jmlr.org
The number of trees T in the random forest (RF) algorithm for supervised learning has to be
set by the user. It is unclear whether T should simply be set to the largest computationally …
set by the user. It is unclear whether T should simply be set to the largest computationally …
MAGSAC++, a fast, reliable and accurate robust estimator
We propose MAGSAC++ and Progressive NAPSAC sampler, P-NAPSAC in short. In
MAGSAC++, we replace the model quality and polishing functions of the original method by …
MAGSAC++, we replace the model quality and polishing functions of the original method by …
Pose estimation for augmented reality: a hands-on survey
E Marchand, H Uchiyama… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Augmented reality (AR) allows to seamlessly insert virtual objects in an image sequence. In
order to accomplish this goal, it is important that synthetic elements are rendered and …
order to accomplish this goal, it is important that synthetic elements are rendered and …