Related papers: Modified Median Statistics and Type Ia Supernova D…
To get distances, Type Ia Supernovae magnitudes are corrected for their correlation with lightcurve width and colour. Here we investigate how this standardisation is affected by the SN environment, with the aim to reduce scatter and improve…
We present a novel class of models for Type Ia supernova time-evolving spectral energy distributions (SED) and absolute magnitudes: they are each modeled as stochastic functions described by Gaussian processes. The values of the SED and…
The question of testing for equality in distribution between two linear models, each consisting of sums of distinct discrete independent random variables with unequal numbers of observations, has emerged from the biological research. In…
The distance and redshift of a type Ia supernova can be determined simultaneously through its multi-band light curves. This fact may be used for imaging surveys that discover and obtain photometry for large numbers of supernovae; so many…
In this paper, we develop modified versions of the likelihood ratio test for multivariate heteroskedastic errors-in-variables regression models. The error terms are allowed to follow a multivariate distribution in the elliptical class of…
Two quantitative tests DIFF1 and DIFF2 for measuring goodness-of-fit between two locally-normalized supernova spectra are presented. Locally-normalized spectra are obtained by dividing a spectrum by the same spectrum smoothed over a…
Type Ia supernovae (SNe Ia) are thermonuclear exploding stars that can be used to put constraints on the nature of our universe. One challenge with population analyses of SNe Ia is Malmquist bias, where we preferentially observe the…
We present new results for consistency of maximum likelihood estimators with a focus on multivariate mixed models. Our theory builds on the idea of using subsets of the full data to establish consistency of estimators based on the full…
We rank the six latest Type Ia supernova (SnIa) datasets (Constitution (C), Union (U), ESSENCE (Davis) (E), Gold06 (G), SNLS 1yr (S) and SDSS-II (D)) in the context of the Chevalier-Polarski-Linder (CPL) parametrization $w(a)=w_0+w_1…
We study characters of recent type Ia supernova (SNIa) data using evolving dark energy models with changing equation of state parameter w. We consider sudden-jump approximation of w for some chosen redshift spans with double transitions,…
The adapted Wasserstein distance $\mathcal{AW}$ is a modification of the classical Wasserstein metric, that provides robust and dynamically consistent comparisons of laws of stochastic processes, and has proved particularly useful in the…
We compare the measured peculiar velocities of 98 local (<150/h Mpc) type Ia supernovae with predictions derived from the PSCz survey. There is excellent agreement between the two datasets with a best fit beta_I (=Omega_m^0.6/b_I) of…
We improve estimates of stellar mass and mass-weighted average age of Type Ia supernova (SN Ia) host galaxies by combining UV and near-IR photometry with optical photometry in our analysis. Using 206 SNe Ia drawn from the full three-year…
We compute the distribution of likelihoods from the non-parametric iterative smoothing method over a set of mock Pantheon-like type Ia supernova datasets. We use this likelihood distribution to test whether typical dark energy models are…
We investigate the effect of microlensing on the standardisation of strongly lensed Type Ia supernovae (GLSNe Ia). We present predictions for the amount of scatter induced by microlensing across a range of plausible strong lens macromodels.…
We study intermediate--z SNe Ia using the empirical physical diagrams which enable to learn about those SNe explosions. This information can be very useful to reduce systematic uncertainties of the Hubble diagram of SNe Ia up to high z. The…
Distribution shifts, where statistical properties differ between training and test datasets, present a significant challenge in real-world machine learning applications where they directly impact model generalization and robustness. In this…
Given the increasing popularity of algorithms for overlapping clustering, in particular in social network analysis, quantitative measures are needed to measure the accuracy of a method. Given a set of true clusters, and the set of clusters…
Based on the median and the median absolute deviation estimators, and the Hodges-Lehmann and Shamos estimators, robustified analogues of the conventional $t$-test statistic are proposed. The asymptotic distributions of these statistics are…
A typical random effects meta-analysis of odds-ratios assumes binomially distributed numbers of events in a treatment and control group and requires the proportion of deaths to be extracted from published papers. This data is often not…