This paper investigates the efficient solution of penalized quadratic regressions in high-dimensional settings.
Computation
The Bayesian image analysis in Fourier space (BIFS) approach proposed here reformulates the conventional Bayesian image analysis paradigm as a large set of independent (but heterogeneous) processes over Fourier space.
Methodology
In the analysis of prognosis studies with time-to-event outcomes, dichotomization of patients is often made.
Methodology Applications
Quantifying the number of deaths caused by the COVID-19 crisis has been an ongoing challenge for scientists, and no golden standard to do so has yet been established.
Applications Methodology
We provide a survey of non-stationary surrogate models which utilize Gaussian processes (GPs) or variations thereof, including non-stationary kernel adaptations, partition and local GPs, and spatial warpings through deep Gaussian processes.
Methodology
Often, it is useful to consider data subset selection at the same time, in which model selection criteria are used to compare models across different subsets of the data.
Methodology High Energy Physics - Lattice
We show that under appropriate conditions on the alignment of source-specific factors, the problem is well-defined and both shared and source-specific factors are identifiable under a constrained matrix factorization objective.
Methodology
CRAN Task Views have been available on the Comprehensive R Archive Network since 2005.
Computation
This paper considers the problem of forecasting mortality rates.
Applications
In economic and financial applications, there is often the need for analysing multivariate time series, comprising of time series for a range of quantities.
Methodology Applications