This paper presents a brief, semi-technical comparison of the essential features of the frequentist and Bayesian approaches to statistical inference, with several illustrative examples implemented in Python. The differences between frequentism and Ba
yesianism fundamentally stem from differing definitions of probability, a philosophical divide which leads to distinct approaches to the solution of statistical problems as well as contrasting ways of asking and answering questions about unknown parameters. After an example-driven discussion of these differences, we briefly compare several leading Python statistical packages which implement frequentist inference using classical methods and Bayesian inference using Markov Chain Monte Carlo.
We explore the utility of Karhunen Loeve (KL) analysis in solving practical problems in the analysis of gravitational shear surveys. Shear catalogs from large-field weak lensing surveys will be subject to many systematic limitations, notably incomple
te coverage and pixel-level masking due to foreground sources. We develop a method to use two dimensional KL eigenmodes of shear to interpolate noisy shear measurements across masked regions. We explore the results of this method with simulated shear catalogs, using statistics of high-convergence regions in the resulting map. We find that the KL procedure not only minimizes the bias due to masked regions in the field, it also reduces spurious peak counts from shape noise by a factor of ~ 3 in the cosmologically sensitive regime. This indicates that KL reconstructions of masked shear are not only useful for creating robust convergence maps from masked shear catalogs, but also offer promise of improved parameter constraints within studies of shear peak statistics.
In modified gravity theories that seek to explain cosmic acceleration, dwarf galaxies in low density environments can be subject to enhanced forces. The class of scalar-tensor theories, which includes f(R) gravity, predict such a force enhancement (m
assive galaxies like the Milky Way can evade it through a screening mechanism that protects the interior of the galaxy from this fifth force). We study observable deviations from GR in the disks of late-type dwarf galaxies moving under gravity. The fifth-force acts on the dark matter and HI gas disk, but not on the stellar disk owing to the self-screening of main sequence stars. We find four distinct observable effects in such disk galaxies: 1. A displacement of the stellar disk from the HI disk. 2. Warping of the stellar disk along the direction of the external force. 3. Enhancement of the rotation curve measured from the HI gas compared to that of the stellar disk. 4. Asymmetry in the rotation curve of the stellar disk. We estimate that the spatial effects can be up to 1 kpc and the rotation velocity effects about 10 km/s in infalling dwarf galaxies. Such deviations are measurable: we expect that with a careful analysis of a sample of nearby dwarf galaxies one can improve astrophysical constraints on gravity theories by over three orders of magnitude, and even solar system constraints by one order of magnitude. Thus effective tests of gravity along the lines suggested by Hui et al (2009) and Jain (2011) can be carried out with low-redshift galaxies, though care must be exercised in understanding possible complications from astrophysical effects.
We present a new method for constructing three-dimensional mass maps from gravitational lensing shear data. We solve the lensing inversion problem using truncation of singular values (within the context of generalized least squares estimation) withou
t a priori assumptions about the statistical nature of the signal. This singular value framework allows a quantitative comparison between different filtering methods: we evaluate our method beside the previously explored Wiener filter approaches. Our method yields near-optimal angular resolution of the lensing reconstruction and allows cluster sized halos to be de-blended robustly. It allows for mass reconstructions which are 2-3 orders-of-magnitude faster than the Wiener filter approach; in particular, we estimate that an all-sky reconstruction with arcminute resolution could be performed on a time-scale of hours. We find however that linear, non-parametric reconstructions have a fundamental limitation in the resolution achieved in the redshift direction.
