Nonparametric Statistics

Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference

WIKS: A general Bayesian nonparametric index for quantifying differences between two populations

Evaluation of probabilistic photometric redshift estimation approaches for LSST

ABC-CDE: Toward Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations

Approximate Bayesian Computation (ABC) is typically used when the likelihood is either unavailable or intractable but where data can be simulated under different parameter settings using a forward model. Despite the recent interest in ABC, …

Comparing two populations using Bayesian Fourier series density estimation

Conditional density estimation using Fourier series and neural networks

Most machine learning tools aim at creating good predictions for new samples. However, obtaining 100% is not feasible in most problems, and therefore modeling the uncertainty over such predictions becomes necessary in several applications. This can …

Photo-z estimation: An example of nonparametric conditional density estimation under selection bias

Redshift is a key quantity for inferring cosmological model parameters. In photometric redshift estimation, cosmologists use the coarse data collected from the vast majority of galaxies to predict the redshift of individual galaxies. To properly …

Converting High-Dimensional Regression to High-Dimensional Conditional Density Estimation

There is a growing demand for nonparametric conditional density estimators (CDEs) in fields such as astronomy and economics. In astronomy, for example, one can dramatically improve estimates of the parameters that dictate the evolution of the …

A unified framework for constructing, tuning and assessing photometric redshift density estimates in a selection bias setting

Photometric redshift estimation is an indispensable tool of precision cosmology. One problem that plagues the use of this tool in the era of large-scale sky surveys is that the bright galaxies that are selected for spectroscopic observation do not …

Nonparametric Conditional Density Estimation in a High-Dimensional Regression Setting.

In some applications (e.g., in cosmology and economics), the regression E[Z|x] is not adequate to represent the association between a predictor x and a response Z because of multi-modality and asymmetry of f(z|x); using the full density instead of a …